diff --git a/.gitignore b/.gitignore
index a706fda..5189e30 100644
--- a/.gitignore
+++ b/.gitignore
@@ -110,3 +110,7 @@ __pycache__/
 *.pyc
 .pytes*t_cache/
 .ruff_cache
+
+# Per-solver checkpoint directories written by run_rcwa.py / run_neviere.py.
+# The unsuffixed checkpoints/ baseline stays tracked; these are scratch.
+validation/*/results/checkpoints_*/
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 090c43c..267c1c1 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,6 +1,50 @@
 # Changelog
 
 ## Unreleased
+
+- Every example that solves now accepts `--solver rcwa|neviere`, defaulting to `rcwa`. Solver-dependent example outputs are suffixed (`*_rcwa.*`, `*_neviere.*`) so the two runs sit side by side; geometry artifacts such as `*_profile.png` stay unsuffixed because they do not depend on the solver.
+- Added three examples covering the cases where the two solvers genuinely differ, rather than duplicating existing examples whose curves would be indistinguishable: `deep_grating_limits` (the modal solver stops at 8.4 wavelengths of depth where the differential method reaches 167), `continuous_vs_staircase` (continuous z-sampling is bit-identical across every `z_resolution_nm`, while a staircase run carries 2.7e-3 of discretization error at 2 nm), and `solver_runtime` (2.4x to 3.0x faster at production resolution, with the solvers still agreeing to ~1e-11).
+- Fixed `multilayer_theta_search` and `blazed_multilayer_memory_comparison` failing with `BrokenProcessPool` on macOS. Both use `max_workers`, and a spawned worker re-imports the script by path; without a `__main__` guard each worker re-ran the whole example and recursively spawned more.
+
+- Fixed `run_multilayer_theta_search_sweep` reporting `solver="rcwa"` on every case regardless of the solver requested. The sweep builds its own `CaseExecutionResult` and copied only the theta-search diagnostics from the underlying result, so `solver` and `solver_options` fell back to their dataclass defaults. The computation was correct throughout -- an rcwa and a neviere sweep differ by ~5e-14 -- but a saved sweep recorded the wrong provenance.
+- Extended the both-solver test coverage to every entry point the examples use: `monochromator_cases`, `energy_angle_cases`, `run_parameter_study`, `run_multilayer_theta_search_sweep`, `assemble_custom_stack`/`LayerSpec`, `AFMGrating`, and the `write_all_orders_csv`/`plot_order_subset`/`efficiency_for_order` output helpers. Swapping `--solver` on any example now exercises a tested path.
+
+- Polarization arguments now accept `TE` and `TM` alongside `s` and `p`, case-insensitively, through a single shared `grax.normalize_polarization`. The library already spoke TE/TM internally (`res0`, `_solve_te_stack`) and in its theory docs while the public API took only s/p; these are the same two states. Values canonicalize to `s`/`p`, so results, CSVs and checkpoints are unchanged. Note the equivalence holds in classical mounting, which is the only mounting this solver supports.
+- The multilayer theta-search workflow now takes `polarization`. It previously had no such argument anywhere, so every theta search ran the `run_simulation` default of `s` -- awkward given all four validation cases run `p`. `run_multilayer_theta_search`, `run_multilayer_theta_search_sweep`, `multilayer_theta_search_cases` and the web form all accept it, and it reaches all three stages of the search. Default stays `s`.
+- `run_parameter_study` now validates `polarization` at the entry point instead of failing several frames deeper inside the simulation wrapper.
+
+### Breaking changes
+
+Renames only — no behaviour changed. Migration:
+
+| old | new |
+| --- | --- |
+| `RCWASimulation` | `GratingSimulation` |
+| `BatchSimulationRunner(default_diffraction_order=)` | `diffraction_order=` |
+| `BatchSimulationRunner(default_fourier_orders=)` | `fourier_orders=` |
+| `BatchSimulationRunner(default_polarization=)` | `polarization=` |
+| `BatchSimulationRunner(default_solver=)` | `solver=` |
+| `neviere_options=` (all entrypoints) | `solver_options=` |
+| `run_simulation(min_efficiency=)` | `min_reflected_efficiency=` |
+
+- Renamed `grax.simulation.RCWASimulation` to `GratingSimulation`. The class drives whichever solver `solver=` selects, so the old name described only one of the two things it can do.
+- Dropped the `default_` prefix from the `BatchSimulationRunner` settings. The prefix was accurate — each of these is the value a case inherits when it omits its own key — but it made `default_fourier_orders: int = 25` read as the default of a default, and the runner's arguments now mirror `run_simulation`'s exactly. The per-case override relationship is documented on each argument instead.
+- Renamed the `neviere_options` argument to `solver_options` everywhere, matching the `solver_options` field already present on results. One name in both directions, and the generic runner no longer names a specific solver in its API. The `NeviereOptions` class keeps its name.
+- Renamed `min_efficiency` to `min_reflected_efficiency` on `run_simulation`, `GratingSimulation` and `run_multilayer_theta_search`. It was half of a min/max pair whose other half was already `max_reflected_efficiency`, and the batch runner had to translate between the two spellings.
+
+- Added a second electromagnetic solver, the Nevière differential method, selectable with `grax.run_simulation(..., solver="neviere")` and `BatchSimulationRunner(default_solver=...)` (per-case `"solver"` also works). It expands the fields in the same truncated Fourier basis as RCWA and applies the same Li/fast-Fourier-factorization rules for TM, but integrates the coupled first-order system in `z` with fourth-order Runge-Kutta instead of eigen-decomposing each layer. Every default stays `"rcwa"`, so existing code, checkpoints and artifacts are unaffected. References: Nevière, Vincent & Petit, *Nouv. Rev. Optique* **5**, 65 (1974); Nevière, *JOSA A* **11**, 1835 (1994); Nevière & Popov, *Light Propagation in Periodic Media* (CRC, 2003).
+- `grax.NeviereOptions` controls the differential method's integration. Step and sub-block sizes are given in optical phase rather than nanometers, so one setting behaves consistently across photon energies, grazing angles and truncation orders. The Fourier truncation order remains the existing `fourier_orders` argument.
+- `NeviereOptions(z_sampling="continuous")` drops the staircase approximation both solvers otherwise share: the permittivity is re-expanded from the true grating profile every `sample_phase` of optical depth, so the result no longer depends on `z_resolution_nm`.
+- The differential method is numerically more robust on deep gratings. The modal solver evaluates `q / sinh(q d)` across a whole layer and overflows above roughly seven wavelengths of depth for a high-contrast lamellar grating; the differential method caps the optical thickness of anything it forms explicitly and still conserves energy to `1e-9` at 167 wavelengths.
+- `SingleSimulationResult` and `CaseExecutionResult` gained a `solver` field, round-tripped through checkpoints so a resumed sweep keeps that provenance.
+- Split the 1D solver into a `grax.solvers` package: `solvers/common.py` holds the shared types, `res0`/`res1`, the Fourier machinery, the layer field operators, the interface cascade and the efficiency extraction; `solvers/rcwa.py` holds the modal layer solve and `res2`; `solvers/neviere.py` holds the differential method. `grax.rcwa_1d` remains as a re-export shim, and the RCWA numerics are unchanged (verified bit-identical across laminar, blazed, multilayer and sinusoidal cases in both polarizations).
+- The batch progress bar now names the solver actually running (`neviere batch`) instead of always printing `RCWA batch`, and the solver-agnostic docstrings on `SingleSimulationResult`, `BatchSimulationRunner`, `gratings.py` and `run_parameter_study` no longer describe themselves as RCWA-specific.
+- Solver selection now reaches every workflow. `run_multilayer_theta_search`, `run_multilayer_theta_search_sweep`, `run_parameter_study`, the `grax_opt` measurement fits and the web UI run form all accept a solver, alongside the existing `run_simulation` and `BatchSimulationRunner` support. Every default stays `"rcwa"`.
+- Fixed the multilayer theta-search workflow silently ignoring `solver=`. `BatchSimulationRunner(default_solver="neviere")` computed those cases with RCWA, with no error or warning, because the workflow's payload carried `backend` but not `solver`. Both runner-settings mappings now come from one place so a new setting cannot reach one execution path and miss the other.
+- `run_parameter_study` gained `backend`, which it previously hardcoded to `"numba"` internally.
+- Results now record `solver_options` alongside `solver`, so a checkpointed differential-method run pins the integration settings that produced it and not just the solver name.
+- Reorganized each validation case into a `grating_definition.py` holding the grating and sweep grid, plus a `run_rcwa.py` and a `run_neviere.py` that import it. Both solvers therefore see identical geometry, energy grid and truncation by construction. Each case's comparison script now overlays both solver curves alongside the external reference codes.
+- Fixed the validation sweep scripts crashing with `BrokenProcessPool` on macOS: the batch runner spawns workers there, and without a `__main__` guard each spawned worker re-ran the whole sweep and recursively spawned more workers.
 - `random-interface` roughness is now a correlated Gaussian random field (Gaussian autocorrelation) instead of per-sample white noise. `grax.RoughnessSpec` gains `correlation_length_nm`: the lateral autocorrelation length in nanometers, defaulting to one tenth of the grating period (`0.0` reproduces the previous white-noise interface). This produces physically smooth interfaces; long correlation lengths (much larger than the grating period) wash out geometrically and are better modelled by the `debye-waller` kind.
 - Added per-layer roughness: `LayerSpec` accepts `roughness_sigma_nm`, and `SingleLayerStack`/`MultilayerStack`/`CustomStack` expose per-layer/per-material roughness arguments (plus a `substrate_roughness_sigma_nm` for the substrate boundary). Each value sets the roughness of that interface, falling back to the grating-level `RoughnessSpec.sigma_nm` when unset. `random-interface` perturbs each interface with its own sigma; per-layer `debye-waller` sigmas combine in quadrature into an effective damping.
 - Web UI: the grating form now has a roughness sigma field for the substrate, each coating layer/material, and the top cap (persisted with the grating, schema v2). The run form has a roughness-kind dropdown (None / Debye-Waller / Random interface) that selects the model applied at run time.
diff --git a/README.md b/README.md
index 28ccd41..c328383 100644
--- a/README.md
+++ b/README.md
@@ -1,15 +1,24 @@
-# grax
+# GraxPy
 
-`grax` is an independent Python package for diffraction-grating simulations in
-X-ray optics, inspired by RETICOLO v9 and extended with higher-level workflows
-for practical studies.
+`graxpy` is an independent Python package for one-dimensional X-ray
+diffraction-grating simulations. Its public Python import is `grax`.
+
+`grax` provides two selectable electromagnetic solver paths:
+
+- modal rigorous coupled-wave analysis (RCWA), inspired by RETICOLO v9;
+- the Nevière differential method.
+
+Both solvers support the same grating, material, and workflow APIs. They share
+the Fourier/discretization infrastructure and differ in how they propagate the
+fields through a layer.
 
 ## Documentation
 
-Full user and API documentation is published online.
+Full user and API documentation is available at
+[graxpy.readthedocs.io](https://graxpy.readthedocs.io/).
 
-- User guide and tutorials: see the project documentation site
-- API reference: see the API section in the documentation site
+- User guide and tutorials: <https://graxpy.readthedocs.io/>
+- API reference: <https://graxpy.readthedocs.io/en/latest/api/index.html>
 
 For local docs builds from this repository, use:
 
@@ -31,7 +40,7 @@ names such as `"Si"` and `"Pt"`, with optional density overrides through
 and xrt-compatible material objects remain supported for now but emit a
 deprecation warning.
 
-PyPI project page: <https://pypi.org/project/graxpy/0.1.0/>
+PyPI project page: <https://pypi.org/project/graxpy/>
 
 For local editable installs:
 
@@ -39,6 +48,40 @@ For local editable installs:
 python -m pip install -e .
 ```
 
+## Select a solver
+
+RCWA is the default, so existing code continues to use it. Pass `solver` to
+choose the Nevière differential method instead:
+
+```python
+import grax
+
+grating = grax.LaminarGrating(
+    period_lpermm=400,
+    width_to_period_ratio=0.67,
+    depth_nm=14.9,
+    substrate_material="Si",
+    layer_material="Pt",
+    layer_thickness_nm=28.77,
+)
+
+common = dict(
+    grating=grating,
+    energy_ev=300.0,
+    grazing_angle_deg=4.0,
+    fourier_orders=30,
+    polarization="p",
+)
+
+rcwa_result = grax.run_simulation(**common, solver="rcwa")
+neviere_result = grax.run_simulation(**common, solver="neviere")
+```
+
+See the documentation's [Choosing a solver](docs/tutorials/choosing-a-solver.md)
+tutorial and the runnable
+`examples/simulation/neviere_solver/neviere_solver.py` for guidance and
+integration options.
+
 ## Local web app
 
 Install the package and web extra, then start the local server.
@@ -107,9 +150,9 @@ overlay for each run. Use `Manage runs` to rename runs or bulk delete them.
 
 ## Attribution
 
-`grax` is inspired by RETICOLO v9. This project is an independent Python
-implementation and is not an official RETICOLO distribution. RETICOLO is not
-bundled as part of the public `graxpy` package distribution.
+The modal RCWA solver is inspired by RETICOLO v9. GraxPy is an independent
+implementation, not an official RETICOLO port or distribution; RETICOLO is not
+bundled with the public `graxpy` package.
 
 - RETICOLO DOI: <https://doi.org/10.5281/zenodo.14631950>
 - RETICOLO license (CC BY 4.0): <https://creativecommons.org/licenses/by/4.0/>
diff --git a/docs/api/simulation/package-organization.md b/docs/api/simulation/package-organization.md
index ce0ffcc..e48a5d8 100644
--- a/docs/api/simulation/package-organization.md
+++ b/docs/api/simulation/package-organization.md
@@ -5,7 +5,7 @@ The `grax.simulation` module is implemented as a package to separate concerns by
 ## Module structure
 
 - `models.py`: Typed result dataclasses (`SingleSimulationResult`, `BatchSimulationResult`, `CaseExecutionResult`, etc.) and small compatibility containers.
-- `core.py`: One-point RCWA execution (`run_simulation`, `RCWASimulation`) and legacy plotting/comparison helpers.
+- `core.py`: One-point solver execution (`run_simulation`, `GratingSimulation`) and legacy plotting/comparison helpers.
 - `batch.py`: Generic batch execution (`BatchSimulationRunner`), checkpointing, subprocess execution, and worker calibration helpers.
 - `cases.py`: Lazy case-generation helpers (`energy_angle_cases`, `fixed_angle_cases`, `monochromator_cases`) and monochromator angle generation.
 - `theta_search.py`: Single-energy multilayer theta-search logic (`run_multilayer_theta_search`) and scan helpers.
diff --git a/docs/api/simulation/single-simulation.md b/docs/api/simulation/single-simulation.md
index fed32e2..cf3a39a 100644
--- a/docs/api/simulation/single-simulation.md
+++ b/docs/api/simulation/single-simulation.md
@@ -1,6 +1,7 @@
 # Single simulation
 
-Core API for one RCWA solve.
+Core API for one electromagnetic grating solve. Select the modal RCWA or
+Nevière differential-method path with `solver=`.
 
 ```{eval-rst}
 .. autofunction:: grax.run_simulation
diff --git a/docs/conf.py b/docs/conf.py
index 5d292e0..163e1c8 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -65,7 +65,7 @@
 }
 
 html_theme = "furo"
-html_static_path = ["_static"]
+html_static_path = ["_static"] if (Path(__file__).resolve().parent / "_static").is_dir() else []
 html_title = "grax documentation"
 templates_path = ["_templates"]
 
diff --git a/docs/developer/index.md b/docs/developer/index.md
index 7050774..71f9af5 100644
--- a/docs/developer/index.md
+++ b/docs/developer/index.md
@@ -1,12 +1,19 @@
 # Developer documentation
 
 This section is for contributors and maintainers who need to understand how the
-high-level API reaches the numerical RCWA implementation.
+high-level API reaches the numerical solvers.
+
+`grax` ships two selectable solver paths behind one interface: modal RCWA and
+the Nevière differential method. They share Fourier/discretization and
+boundary-response infrastructure, but use different layer-propagation methods.
+Read [RCWA theory](rcwa-theory.md) and the
+[Nevière differential method](neviere-theory.md) together for the two paths.
 
 ```{toctree}
 :maxdepth: 1
 
 rcwa-theory
+neviere-theory
 physics-to-code
 solver-flow
 module-guide
diff --git a/docs/developer/module-guide.md b/docs/developer/module-guide.md
index 216f916..883f33b 100644
--- a/docs/developer/module-guide.md
+++ b/docs/developer/module-guide.md
@@ -14,7 +14,7 @@ This guide summarizes the source layout for contributors.
 - `stacks.py`: coating stack models above the substrate surface
 - `simulation/`: simulation workflows and orchestration (see package organization)
   - `models.py`: typed result dataclasses and small compatibility containers
-  - `core.py`: one-point RCWA execution and legacy plotting/comparison helpers
+  - `core.py`: one-point solver dispatch and legacy plotting/comparison helpers
   - `batch.py`: generic batch execution, checkpointing, subprocess execution, and worker calibration helpers
   - `cases.py`: lazy case-generation helpers and monochromator angle generation
   - `theta_search.py`: single-energy multilayer theta-search logic and scan helpers
@@ -22,9 +22,16 @@ This guide summarizes the source layout for contributors.
   - `serialization.py`: JSON/checkpoint serialization for single and case results
 - `parameter_sweep.py`: repeated simulations for numerical convergence and
   parameter studies
-- `rcwa_1d.py`: native one-dimensional TE-style RCWA numerical core
+- `solvers/`: the one-dimensional electromagnetic solvers
+  - `common.py`: shared types, `res0`/`res1`, the Fourier machinery, the layer
+    field operators (including the Li/fast-Fourier-factorization rules for TM),
+    the interface-response cascade, and the efficiency extraction
+  - `rcwa.py`: modal (eigen-decomposed) layer solve and `res2`
+  - `neviere.py`: Nevière differential method, `res2_dm`, and `NeviereOptions`
+- `rcwa_1d.py`: re-export shim keeping the historical `grax.rcwa_1d` import path
+  working. New code should import from `grax.solvers`
 - `roughness.py`: roughness post-processing models and diagnostics (currently
-  scalar Debye-Waller damping used by `rcwa_1d.res2()`)
+  scalar Debye-Waller damping applied by both solvers)
 - `slag.py`: legacy SLAG convenience helpers built on the generic public API
 
 ## Optimization package
@@ -48,15 +55,22 @@ to a scalar complex refractive index at a requested photon energy.
 Change `simulation/` when user-facing orchestration, result packaging,
 checkpointing, plotting, or validation behavior changes.
 
-Change `rcwa_1d.py` when the Fourier conversion, stack solve, polarization
-support, or diffraction-output calculation changes. Change `roughness.py` when
-roughness model math or diagnostics change.
+Change `solvers/common.py` when the Fourier conversion, the layer field
+operators, the interface cascade, or the diffraction-output calculation changes:
+that code is shared, so both solvers move together. Change `solvers/rcwa.py` or
+`solvers/neviere.py` only when one solver's own propagation changes. Adding a
+third solver means supplying a per-layer block builder to
+`solve_stack_from_layer_blocks()` and extending `SOLVER_NAMES` in
+`simulation/core.py`.
+
+Change `roughness.py` when roughness model math or diagnostics change.
 
 ## Reading order for new maintainers
 
-1. `examples/manual_single_simulation_example/manual_single_simulation.py`
+1. `examples/simulation/single_simulation/single_simulation.py`
 2. `examples/simulation/fixed_angle_sweep/fixed_angle_sweep.py`
 3. `src/grax/simulation/` (package overview in docs/api/simulation/package-organization.md)
 4. `src/grax/gratings.py`
 5. `src/grax/materials.py` and `src/grax/stacks.py`
-6. `src/grax/rcwa_1d.py`
+6. `src/grax/solvers/` (start with `common.py`, then read `rcwa.py` and
+   `neviere.py` as the two propagation implementations)
diff --git a/docs/developer/neviere-theory.md b/docs/developer/neviere-theory.md
new file mode 100644
index 0000000..ca874e4
--- /dev/null
+++ b/docs/developer/neviere-theory.md
@@ -0,0 +1,169 @@
+# Nevière differential method
+
+The differential method is one of `grax`'s two selectable electromagnetic solver
+paths, selected with `solver="neviere"`. It solves the same physical problem as the RCWA solver in
+[RCWA theory](rcwa-theory.md) and shares most of its machinery; this page
+describes only what differs and why the two agree.
+
+The method is due to Nevière, Vincent and Petit {cite}`neviere1974differential`,
+extended to multilayer (Bragg–Fresnel) stacks in {cite}`neviere1994multilayer`,
+and treated at length in {cite}`neviere2003light`.
+
+## What differs from RCWA
+
+Both solvers expand the fields and the permittivity in the same truncated
+Fourier basis along `x`, and both reduce one grating period to a set of coupled
+ordinary differential equations in the depth direction `z`. They differ in one
+step only:
+
+- **RCWA** treats each layer as invariant in `z`, eigen-decomposes its field
+  operator once, and propagates the layer analytically through the resulting
+  modal exponentials.
+- **The differential method** integrates the coupled system numerically in `z`
+  with a fourth-order Runge–Kutta scheme, without ever forming the modes.
+
+Everything before that step (`res1`, the Fourier coefficients, the layer field
+operators) and everything after it (the interface cascade, the Rayleigh
+expansion in the semi-infinite media, the Poynting-flux efficiencies) is one
+shared implementation in `grax.solvers.common`.
+
+## The coupled system
+
+Write `F` for the tangential field that is continuous across every interface,
+and `G` for its conjugate tangential partner:
+
+| Polarization | `F` | `G` |
+| --- | --- | --- |
+| TE (`s`) | `E_y` | `dE_y/dz` |
+| TM (`p`) | `H_y` | `E_x = [[1/ε]] dH_y/dz` |
+
+Maxwell's equations then reduce to a first-order system in the Fourier
+coefficients:
+
+```
+d/dz [F; G] = [[0, A], [B, 0]] [F; G]
+```
+
+with
+
+- **TE:** `A = I`, `B = Kx² − k0² [[ε]]`
+- **TM:** `A = [[1/ε]]⁻¹`, `B = Kx [[ε]]⁻¹ Kx − k0² I`
+
+where `Kx = diag(kx_m)` holds the in-plane wavevector of each retained order and
+`[[·]]` denotes a Toeplitz convolution matrix built from Fourier coefficients.
+
+Eliminating `G` recovers the second-order form `d²F/dz² = (A·B) F`, and `A·B` is
+exactly the operator the RCWA solver eigen-decomposes. That is the reason the
+two solvers agree: they are two numerical treatments of one system, not two
+models.
+
+## Fast Fourier factorization
+
+The TM operators above are not the naive Laurent products. `[[ε]]⁻¹` and
+`[[1/ε]]⁻¹` are different matrices, and using the wrong one is the classic cause
+of the differential method's notoriously slow TM convergence. The rules applied
+here are Li's {cite}`li1996formulation`, in the form Popov and Nevière give for
+the differential method {cite}`popov2000gratingtheory`: the inverse rule for the
+product of the discontinuous permittivity with the discontinuous normal field
+component, and the direct rule where both factors are continuous.
+
+In the code these operators come from `layer_field_operators()`, shared with
+RCWA, so the factorization is inherited rather than re-derived.
+
+## Numerical stability
+
+A transfer matrix across a whole grating grows like `exp(|q| d)` in the
+evanescent orders, which overflows for anything but shallow structures. The
+solver therefore never forms one:
+
+1. Each layer is split into sub-blocks whose optical thickness `|q| d` is capped
+   by `NeviereOptions.block_phase`. `|q|` is bounded per layer from the row norm
+   of the layer operator, which is tight for the low-contrast permittivities of
+   X-ray optics.
+2. Each sub-block is integrated with Runge–Kutta into a transfer matrix, then
+   immediately converted into a Dirichlet-to-Neumann interface-response block
+   mapping `[F_top; F_bottom]` to `[G_top; G_bottom]`.
+3. Blocks are combined with `_cascade_boundary_pair()`, which eliminates the
+   shared interface field through a linear solve.
+
+Step 3 is an R-matrix (impedance) propagation, not a transfer-matrix product, so
+no growing exponential is ever accumulated across the stack. The conversion in
+step 2 reproduces the modal block `[[-q coth(qd), q csch(qd)], [-q csch(qd), q
+coth(qd)]]` exactly for a homogeneous slab, which is a useful check when reading
+the code.
+
+In practice this makes the differential method the more robust of the two on
+deep structures: the modal solver evaluates `q / sinh(q d)` across a full layer
+and overflows above roughly seven wavelengths of depth for a high-contrast
+lamellar grating, where the differential method still conserves energy to `1e-9`
+at 167 wavelengths.
+
+## Choosing the step size
+
+Step and sub-block sizes are expressed in optical phase rather than nanometers,
+so one setting behaves consistently across photon energies, grazing angles and
+truncation orders:
+
+- `step_phase` bounds `|q| h` for one Runge–Kutta step. Accuracy improves as its
+  fourth power, while cost grows far more slowly, because most of the per-layer
+  work is the interface conversion and cascade rather than the Runge–Kutta
+  stages.
+- `block_phase` bounds `|q| d` for one explicitly formed transfer matrix. It
+  trades conditioning only; the converged answer does not depend on it.
+
+The Fourier truncation order is the existing `fourier_orders` argument, retaining
+`2·fourier_orders + 1` components. There is no separate truncation setting for
+this solver.
+
+## Sampling the permittivity along z
+
+`NeviereOptions.z_sampling` selects where `ε(x, z)` comes from:
+
+- `"textures"` (default) integrates through the same z-sliced permittivity RCWA
+  uses, so the two solvers see byte-identical geometry and any difference between
+  them is Runge–Kutta truncation error alone. This is the mode used for
+  cross-validation.
+- `"continuous"` re-expands `ε(x, z)` from the true grating profile at every
+  sub-block, which is the textbook differential method. It drops the staircase
+  approximation entirely: its result does not depend on `z_resolution_nm` at all,
+  and it reaches the z-converged answer more cheaply than refining the staircase
+  does.
+
+`"continuous"` needs the grating object to sample the profile between solver
+rows, so it is selected through `grax.run_simulation`, which builds the sampler
+with `build_grating_epsilon_sampler()`.
+
+## Energy balance
+
+`propagating_energy_balance()` sums the propagating reflected and transmitted
+orders. For a lossless structure the total is one; the absorbing materials used
+in the X-ray regime make it legitimately smaller, and the shortfall is the
+absorbed fraction rather than a solver error. Only an upper bound is enforced,
+through `NeviereOptions.energy_balance_tolerance`.
+
+## Internal solver reference
+
+```{autoclass} grax.solvers.neviere.NeviereOptions
+:members:
+```
+
+```{autofunction} grax.solvers.neviere.res2_dm
+```
+
+```{autofunction} grax.solvers.neviere.build_grating_epsilon_sampler
+```
+
+```{autoclass} grax.solvers.neviere.EpsilonSampler
+:members:
+```
+
+```{autofunction} grax.solvers.common.layer_field_operators
+```
+
+```{autofunction} grax.solvers.common.solve_stack_from_layer_blocks
+```
+
+```{autofunction} grax.solvers.common.propagating_energy_balance
+```
+
+The full bibliography is rendered on the [RCWA theory](rcwa-theory.md) page.
diff --git a/docs/developer/physics-to-code.md b/docs/developer/physics-to-code.md
index 0297468..8e15141 100644
--- a/docs/developer/physics-to-code.md
+++ b/docs/developer/physics-to-code.md
@@ -13,14 +13,14 @@ orientation point when changing solver behavior.
 | Coating sequence | `SingleLayerStack`, `MultilayerStack` | `grax.stacks` | Defines material layers above the substrate surface |
 | Direct simulation | `run_simulation` | `grax.simulation` | Converts user settings into wavelength, wave vector, textures, and solver calls |
 | Batch orchestration | `BatchSimulationRunner` | `grax.simulation` | Streams case dictionaries through the single-case solver and yields `CaseExecutionResult` values |
-| Fourier texture conversion | `res1()` | `grax.rcwa_1d` | Converts material textures into Fourier-space texture data |
-| Stack solution | `res2()` | `grax.rcwa_1d` | Solves reflected and transmitted diffraction orders |
-| Diffraction outputs | `DiffractionResult`, `Res2Result` | `grax.rcwa_1d` | Carries orders, angles, amplitudes, and efficiencies back to `simulation.py` |
+| Fourier texture conversion | `res1()` | `grax.solvers` | Converts material textures into Fourier-space texture data |
+| Stack solution | `res2()` | `grax.solvers` | Solves reflected and transmitted diffraction orders |
+| Diffraction outputs | `DiffractionResult`, `Res2Result` | `grax.solvers` | Carries orders, angles, amplitudes, and efficiencies back to `simulation.py` |
 
 ## Public boundary
 
 The practical public boundary is `grax.__init__`. User-facing docs should
-prefer symbols exported there. The `grax.rcwa_1d` module remains important
+prefer symbols exported there. The `grax.solvers` module remains important
 for contributors, but it is not the first interface users should learn.
 
 ## Geometry and materials
diff --git a/docs/developer/rcwa-theory.md b/docs/developer/rcwa-theory.md
index 511f76e..358b748 100644
--- a/docs/developer/rcwa-theory.md
+++ b/docs/developer/rcwa-theory.md
@@ -2,8 +2,9 @@
 
 Rigorous coupled-wave analysis models diffraction from periodic structures by
 expanding the electromagnetic fields and material permittivity in Fourier
-orders. In `grax`, the native solver path is currently a one-dimensional
-TE-style implementation for periodic grating profiles used in x-ray optics.
+orders. In `grax`, modal RCWA is one of two selectable electromagnetic solver
+paths; it is a one-dimensional implementation for periodic grating profiles
+used in X-ray optics and is inspired by RETICOLO.
 
 This page gives the minimum physical model needed to understand the code. It is
 not a replacement for RCWA references such as {cite}`moharam1995stable` and
diff --git a/docs/developer/solver-flow.md b/docs/developer/solver-flow.md
index 431af4b..6e35ca1 100644
--- a/docs/developer/solver-flow.md
+++ b/docs/developer/solver-flow.md
@@ -3,6 +3,11 @@
 This page follows the execution path from public API calls to the numerical
 solver routines.
 
+Two solvers sit at the end of that path. They share every step except the one
+that turns a finite layer into an interface-response block, so the flow below is
+identical for both; only step 12 branches. See
+[Nevière differential method](neviere-theory.md) for what that branch does.
+
 ## Direct one-point workflow
 
 1. The user creates a grating, usually {class}`grax.LaminarGrating` or
@@ -24,9 +29,13 @@ solver routines.
 9. `run_simulation()` calls `res1(wavelength, period, textures, fourier_orders, k_parallel, parm)`.
 10. `res1()` normalizes diffraction orders and converts raw textures into
     `Texture1D` objects with Fourier coefficients.
-11. `run_simulation()` calls `res2(aa, profile, parm, roughness_sigma_nm=...)`.
-12. `res2()` validates the profile, compresses adjacent identical textures, and
-    solves the TE stack.
+11. `run_simulation()` calls `res2(aa, profile, parm, roughness_sigma_nm=...)`,
+    or `res2_dm(...)` when `solver="neviere"`.
+12. The chosen solver validates the profile, compresses adjacent identical
+    textures, builds one interface-response block per layer, and hands them to
+    the shared `solve_stack_from_layer_blocks()`. RCWA builds each block by
+    eigen-decomposing the layer operator; the differential method builds it by
+    integrating the equivalent first-order system in `z`.
 13. `res2()` optionally applies scalar Debye-Waller roughness damping for
     solver-level roughness.
 14. `run_simulation()` finds the requested reflected diffraction order, validates
@@ -78,6 +87,7 @@ Important runtime checks include:
 - `res2()` rejects invalid profile arrays.
 - The native Python path currently rejects unsupported dimensions and
   polarizations.
+- `run_simulation` rejects an unknown `solver` name before doing any work.
 
 ## Memory-mode policy
 
@@ -93,23 +103,28 @@ as a public performance option.
 
 These functions are developer-facing numerical entry points:
 
-```{autofunction} grax.rcwa_1d.res0
+```{autofunction} grax.solvers.common.res0
+```
+
+```{autofunction} grax.solvers.common.res1
 ```
 
-```{autofunction} grax.rcwa_1d.res1
+```{autofunction} grax.solvers.rcwa.res2
 ```
 
-```{autofunction} grax.rcwa_1d.res2
+```{autofunction} grax.solvers.neviere.res2_dm
 ```
 
-```{autoclass} grax.rcwa_1d.Res1Result
+```{autoclass} grax.solvers.common.Res1Result
 :members:
 ```
 
-```{autoclass} grax.rcwa_1d.Res2Result
+```{autoclass} grax.solvers.common.Res2Result
 :members:
 ```
 
-```{autoclass} grax.rcwa_1d.DiffractionResult
+```{autoclass} grax.solvers.common.DiffractionResult
 :members:
 ```
+
+The historical `grax.rcwa_1d` import path still resolves all of these names.
diff --git a/docs/how-to/images/sinusoidal_custom_profile.png b/docs/how-to/images/sinusoidal_custom_profile.png
index 052c31a..36c1f80 100644
Binary files a/docs/how-to/images/sinusoidal_custom_profile.png and b/docs/how-to/images/sinusoidal_custom_profile.png differ
diff --git a/docs/how-to/user-defined-cases.md b/docs/how-to/user-defined-cases.md
index bd68011..543a5ff 100644
--- a/docs/how-to/user-defined-cases.md
+++ b/docs/how-to/user-defined-cases.md
@@ -57,8 +57,8 @@ when omitted.
 
 ```python
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=diffraction_order,
-    default_fourier_orders=25,
+    diffraction_order=diffraction_order,
+    fourier_orders=25,
     show_progress=True,
     on_error="continue",
 )
diff --git a/docs/index.md b/docs/index.md
index 6f4aed4..fbaf39b 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -2,15 +2,30 @@
 
 *Version {{ release }}*
 
-`grax` is an independent Python package for one-dimensional RCWA simulations of X-ray diffraction gratings. The current solver implementation is inspired by the one-dimensional RETICOLO approach and currently supports 1D RCWA simulations, including multilayer coating stacks.
+`graxpy` is an independent Python package for one-dimensional X-ray
+diffraction-grating simulations; `grax` is its public Python import. It offers
+two selectable electromagnetic solver paths for the same gratings, materials,
+and workflows:
 
-On top of the RCWA solver, `grax` provides higher-level abstractions to define and simulate different grating geometries, currently including laminar and blazed gratings, together with user-friendly simulation utilities for single simulations, batch execution, and energy-angle sweeps.
+- modal rigorous coupled-wave analysis (RCWA), inspired by the one-dimensional
+  RETICOLO approach;
+- the Nevière differential method.
+
+The paths share Fourier/discretization infrastructure and differ in how they
+propagate fields through a layer. `solver="rcwa"` remains the default. `grax`
+provides higher-level abstractions for laminar and blazed gratings, multilayer
+coating stacks, single simulations, batch execution, and energy-angle sweeps.
+
+For selection guidance and integration settings, see
+[Choosing a solver](tutorials/choosing-a-solver.md).
 
 The local Web UI includes its own documentation page. Start `grax-web`, then click
 `Web docs` in the GUI to read the guide for storage, grating creation,
 simulation runs, plotting, exporting, and customization.
 
-RETICOLO V9 is an important scientific reference and inspiration for this project. `grax` is not an official RETICOLO port or direct translation. If you use `grax`, please also cite RETICOLO:
+RETICOLO V9 is an important scientific reference and inspiration for GraxPy's
+modal RCWA solver. `grax` is not an official RETICOLO port or direct
+translation. If you use `grax`, please also cite RETICOLO:
 
 > [https://doi.org/10.5281/zenodo.14631950](https://doi.org/10.5281/zenodo.14631950)
 
diff --git a/docs/installation/index.md b/docs/installation/index.md
index 2437c7a..b80c904 100644
--- a/docs/installation/index.md
+++ b/docs/installation/index.md
@@ -57,9 +57,12 @@ python -m pip install -e ".[opt]"
 ```
 
 ```{note}
-The numba backend provides **3.7x speedup** with identical numerical results.
-You can still explicitly specify `backend="numpy"` for parity checks or
-transition-time comparisons, but that path is deprecated.
+Numba accelerates the shared Fourier-coefficient calculation used by both
+electromagnetic solver paths. The resulting speedup depends on the grating,
+Fourier order, and machine; the checked-in benchmarks provide representative
+measurements. It does not JIT the RCWA modal solve or the Nevière differential
+propagation. You can still explicitly specify `backend="numpy"` for parity
+checks or transition-time comparisons, but that path is deprecated.
 ```
 
 The main documentation focuses on the `grax` simulation package. The
diff --git a/docs/references.bib b/docs/references.bib
index 0cbc151..77fe9a3 100644
--- a/docs/references.bib
+++ b/docs/references.bib
@@ -17,3 +17,41 @@ @article{li1996formulation
   number = {9},
   pages = {1870--1876}
 }
+
+@article{neviere1974differential,
+  author = {Nevière, M. and Vincent, P. and Petit, R.},
+  title = {Sur la théorie du réseau conducteur et ses applications à l'optique},
+  journal = {Nouvelle Revue d'Optique},
+  year = {1974},
+  volume = {5},
+  number = {2},
+  pages = {65--77}
+}
+
+@article{neviere1994multilayer,
+  author = {Nevière, M.},
+  title = {Bragg-Fresnel multilayer gratings: electromagnetic theory},
+  journal = {Journal of the Optical Society of America A},
+  year = {1994},
+  volume = {11},
+  number = {5},
+  pages = {1835--1845}
+}
+
+@book{neviere2003light,
+  author = {Nevière, Michel and Popov, Evgeny},
+  title = {Light Propagation in Periodic Media: Differential Theory and Design},
+  publisher = {CRC Press},
+  address = {Boca Raton},
+  year = {2003}
+}
+
+@article{popov2000gratingtheory,
+  author = {Popov, E. and Nevière, M.},
+  title = {Grating theory: new equations in Fourier space leading to fast converging results for {TM} polarization},
+  journal = {Journal of the Optical Society of America A},
+  year = {2000},
+  volume = {17},
+  number = {10},
+  pages = {1773--1784}
+}
diff --git a/docs/tutorials/acceleration-backend/activate-numba-backend.md b/docs/tutorials/acceleration-backend/activate-numba-backend.md
index 4a059c1..0846dab 100644
--- a/docs/tutorials/acceleration-backend/activate-numba-backend.md
+++ b/docs/tutorials/acceleration-backend/activate-numba-backend.md
@@ -6,8 +6,10 @@ Install `graxpy` normally. The numba backend is part of the standard package:
 python -m pip install graxpy
 ```
 
-Most user-facing solver calls already default to `backend="numba"`. You can
-still pass it explicitly when you want the choice to be visible in a script:
+Most user-facing solver calls already default to `backend="numba"`. It
+accelerates the Fourier-coefficient calculation shared by RCWA and Nevière,
+before either path propagates fields through the grating. You can still pass it
+explicitly when you want the choice to be visible in a script:
 
 ```python
 import grax
diff --git a/docs/tutorials/batch-simulations.md b/docs/tutorials/batch-simulations.md
index 4f86399..b7cdc6d 100644
--- a/docs/tutorials/batch-simulations.md
+++ b/docs/tutorials/batch-simulations.md
@@ -14,9 +14,9 @@ Minimal pattern:
 
 ```python
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=25,
-    default_polarization="p",
+    diffraction_order=1,
+    fourier_orders=25,
+    polarization="p",
     show_progress=True,
     on_error="continue",
 )
diff --git a/docs/tutorials/checkpoints-and-resume.md b/docs/tutorials/checkpoints-and-resume.md
index 34f2d58..5c065a4 100644
--- a/docs/tutorials/checkpoints-and-resume.md
+++ b/docs/tutorials/checkpoints-and-resume.md
@@ -6,9 +6,9 @@ Use checkpointing when a batch run is long or may be interrupted.
 
 ```python
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=25,
-    default_polarization="p",
+    diffraction_order=1,
+    fourier_orders=25,
+    polarization="p",
     checkpoint_dir="results/checkpoints",
     checkpoint_interval=1,
     resume=True,
diff --git a/docs/tutorials/choosing-a-solver.md b/docs/tutorials/choosing-a-solver.md
new file mode 100644
index 0000000..eda0723
--- /dev/null
+++ b/docs/tutorials/choosing-a-solver.md
@@ -0,0 +1,185 @@
+# Choosing a solver
+
+`grax` ships two selectable electromagnetic solver paths behind one interface:
+modal RCWA and the Nevière differential method. They share Fourier,
+discretization, and output machinery, but use different layer-propagation
+methods. Every entry point takes a `solver` argument and defaults to `"rcwa"`,
+so existing code keeps its current behaviour.
+
+```python
+import grax
+
+grating = grax.LaminarGrating(
+    period_lpermm=400,
+    width_to_period_ratio=0.67,
+    depth_nm=14.9,
+    left_wall_angle_deg=15.0,
+    right_wall_angle_deg=15.0,
+    substrate_material="Si",
+    layer_material="Pt",
+    layer_thickness_nm=28.77,
+    x_resolution_nm=1.0,
+    z_resolution_nm=0.1,
+)
+
+common = dict(
+    grating=grating,
+    energy_ev=300.0,
+    grazing_angle_deg=4.0,
+    fourier_orders=30,
+    polarization="p",
+)
+
+rcwa = grax.run_simulation(**common, solver="rcwa")
+neviere = grax.run_simulation(**common, solver="neviere")
+
+print(rcwa.selected_efficiency, neviere.selected_efficiency)
+```
+
+Each result records which solver produced it:
+
+```python
+assert neviere.solver == "neviere"
+```
+
+## Which one to use
+
+`"rcwa"` remains the default and is the right choice unless you have a specific
+reason to switch.
+
+Reach for `"neviere"` when you want to:
+
+- **Cross-check a result.** The two solvers share their Fourier operators and
+  their efficiency extraction but propagate through the grating by completely
+  different numerics, so agreement is meaningful evidence and disagreement
+  localises quickly.
+- **Model a deep grating.** The modal solver evaluates `q / sinh(q d)` across a
+  whole layer and overflows above roughly seven wavelengths of depth for a
+  high-contrast profile. The differential method caps the optical thickness of
+  anything it forms explicitly and stays stable far beyond that.
+- **Remove the staircase approximation.** With `z_sampling="continuous"` the
+  permittivity is read from the true profile instead of the z-sliced
+  approximation of it (see below).
+
+For the shallow X-ray gratings in `validation/`, the two agree to about `1e-10`
+in absolute efficiency, and the differential method runs two to five times
+faster because it never eigen-decomposes a layer.
+
+## Batch runs
+
+The batch runner takes a default and each case can override it:
+
+```python
+runner = grax.BatchSimulationRunner(
+    fourier_orders=30,
+    solver="neviere",
+)
+
+cases = grax.fixed_angle_cases(
+    grating=grating,
+    energies_ev=[200.0, 300.0, 400.0],
+    grazing_angle_deg=4.0,
+    polarization="p",
+)
+
+# Or per case, to run both solvers over the same sweep:
+mixed = [dict(case, solver=solver) for case in cases for solver in ("rcwa", "neviere")]
+```
+
+The solver is stored in every {class}`grax.CaseExecutionResult` and round-trips
+through checkpoints, so a resumed sweep keeps that provenance.
+
+## Tuning the differential method
+
+{class}`grax.NeviereOptions` controls the integration. The defaults are chosen to
+put the residual against RCWA well below any physically meaningful level, so you
+should rarely need to change them.
+
+```python
+result = grax.run_simulation(
+    **common,
+    solver="neviere",
+    solver_options=grax.NeviereOptions(step_phase=0.005),
+)
+```
+
+| Option | Meaning |
+| --- | --- |
+| `step_phase` | Optical phase per Runge–Kutta step. Accuracy improves as its fourth power; cost grows far more slowly. |
+| `block_phase` | Optical phase per explicitly formed transfer matrix. Affects conditioning only, not the converged answer. |
+| `max_step_nm` | Optional hard cap on the step in nanometers, on top of `step_phase`. |
+| `z_sampling` | `"textures"` (default) or `"continuous"`. |
+| `energy_balance_tolerance` | Upper bound on the summed propagating efficiency; raises when exceeded. |
+
+The Fourier truncation order is the ordinary `fourier_orders` argument, shared
+with the RCWA solver. There is no separate setting for this solver.
+
+A mapping works anywhere an options object does, which is convenient in case
+dictionaries:
+
+```python
+case = dict(case, solver="neviere", solver_options={"step_phase": 0.005})
+```
+
+## Continuous permittivity sampling
+
+Both solvers normally slice the grating into layers of `z_resolution_nm` and
+treat the permittivity as constant within each. That staircase is a
+discretization error you pay for by refining `z_resolution_nm`, which makes every
+solve more expensive.
+
+The differential method can skip it:
+
+```python
+result = grax.run_simulation(
+    **common,
+    solver="neviere",
+    solver_options=grax.NeviereOptions(z_sampling="continuous"),
+)
+```
+
+In this mode the permittivity is re-expanded from the true grating profile at
+every sub-block, so the result does not depend on `z_resolution_nm` at all. On a
+sinusoidal test profile the continuous result matched a staircase converged at
+`z_resolution_nm = 0.005`, while the staircase solvers at `z_resolution_nm = 0.1`
+were still an order of magnitude further away.
+
+Use `"textures"` (the default) when you are comparing against RCWA, since it
+guarantees both solvers see identical geometry. Use `"continuous"` when you want
+the profile itself resolved rather than its staircase approximation.
+
+## Where the solver argument works
+
+Solver selection reaches every workflow, not just one-point solves:
+
+| entrypoint | how to select |
+| --- | --- |
+| {func}`grax.run_simulation` | `solver=`, `solver_options=` |
+| {class}`grax.GratingSimulation` | `solver=`, `solver_options=` |
+| {class}`grax.BatchSimulationRunner` | `solver=`, `solver_options=`, or a per-case `"solver"` key |
+| {func}`grax.run_multilayer_theta_search` | `solver=` — used for all three scan stages |
+| {func}`grax.run_multilayer_theta_search_sweep` | `solver=` |
+| {func}`grax.run_parameter_study` | `solver=` |
+| `grax_opt` measurement fits | `solver` / `solver_options` on the config |
+| Web UI | Solver dropdown in the run form |
+
+Every default is `"rcwa"`, so existing code is unaffected.
+
+Each result records the solver that produced it, and — for the differential
+method — the integration settings, so a checkpoint or saved run is reproducible:
+
+```python
+result.solver          # "neviere"
+result.solver_options  # {"z_sampling": "textures", "step_phase": 0.02, ...}
+```
+
+See `examples/simulation/neviere_solver/neviere_solver.py` for a runnable
+one-point and energy-sweep comparison, and
+[Nevière differential method](../developer/neviere-theory.md) for the underlying
+formulation.
+
+## Seeing the difference
+
+The three specialist examples in {doc}`solver-difference-examples` cover the
+cases where the choice actually changes something: depth range, staircase
+versus continuous z-sampling, and runtime.
diff --git a/docs/tutorials/energy-angle-sweep.md b/docs/tutorials/energy-angle-sweep.md
index b6d8052..facc0a5 100644
--- a/docs/tutorials/energy-angle-sweep.md
+++ b/docs/tutorials/energy-angle-sweep.md
@@ -10,7 +10,7 @@ row every 50 points for faster execution.
 - Sampling: every 50 rows
 - `x_resolution_nm = 1.0`
 - `z_resolution_nm = 1.0`
-- `default_fourier_orders = 5`
+- `fourier_orders = 5`
 
 ```python
 from pathlib import Path
@@ -61,8 +61,8 @@ cases = grax.energy_angle_cases(
 )
 
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=2,
-    default_fourier_orders=5,
+    diffraction_order=2,
+    fourier_orders=5,
     show_progress=True,
     live_plot=False,
     on_error="fail_fast",
diff --git a/docs/tutorials/export-and-plot-results.md b/docs/tutorials/export-and-plot-results.md
index 87d68b9..757d34d 100644
--- a/docs/tutorials/export-and-plot-results.md
+++ b/docs/tutorials/export-and-plot-results.md
@@ -17,7 +17,7 @@ import grax
 # results can come from run_simulation(), runner.run_cases(), or a single case
 grax.write_all_orders_csv(
     results,
-    "examples/simulation/fixed_angle_sweep/results/fixed_angle_all_orders.csv",
+    "examples/simulation/fixed_angle_sweep/results/fixed_angle_all_orders_rcwa.csv",
 )
 ```
 
@@ -49,7 +49,7 @@ import grax
 
 grax.plot_order_subset(
     results,
-    "examples/simulation/fixed_angle_sweep/results/fixed_angle_orders_1_3.png",
+    "examples/simulation/fixed_angle_sweep/results/fixed_angle_orders_1_3_rcwa.png",
     diffraction_orders=[1, 2, 3],
     title="Fixed-Angle Sweep: Orders 1-3 Efficiency vs Energy",
 )
@@ -63,7 +63,7 @@ You can post-process exported CSV files directly:
 import pandas as pd
 
 data = pd.read_csv(
-    "examples/simulation/fixed_angle_sweep/results/fixed_angle_all_orders.csv"
+    "examples/simulation/fixed_angle_sweep/results/fixed_angle_all_orders_rcwa.csv"
 )
 
 # Keep first diffraction order
diff --git a/docs/tutorials/fixed-angle-sweep.md b/docs/tutorials/fixed-angle-sweep.md
index 7e68a3e..91fc5a5 100644
--- a/docs/tutorials/fixed-angle-sweep.md
+++ b/docs/tutorials/fixed-angle-sweep.md
@@ -29,8 +29,8 @@ cases = grax.fixed_angle_cases(
 )
 
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=20,
+    diffraction_order=1,
+    fourier_orders=20,
     show_progress=True,
     live_plot=True,
     live_plot_x_key="energy_ev",
@@ -39,10 +39,10 @@ runner = grax.BatchSimulationRunner(
 )
 
 results = list(runner.run_cases(cases))
-grax.write_all_orders_csv(results, "examples/simulation/fixed_angle_sweep/results/fixed_angle_all_orders.csv")
+grax.write_all_orders_csv(results, "examples/simulation/fixed_angle_sweep/results/fixed_angle_all_orders_rcwa.csv")
 grax.plot_order_subset(
     results,
-    "examples/simulation/fixed_angle_sweep/results/fixed_angle_orders_1_3.png",
+    "examples/simulation/fixed_angle_sweep/results/fixed_angle_orders_1_3_rcwa.png",
     diffraction_orders=[1, 2, 3],
     title="Fixed-Angle Sweep: Orders 1-3 Efficiency vs Energy",
 )
@@ -66,16 +66,13 @@ generated case. Accepted polarization values are `s` and `p`.
 
 See `examples/simulation/fixed_angle_sweep/fixed_angle_sweep.py` for the complete script.
 
-For a roughness-specific variant, see
-`examples/simulation/fixed_angle_roughness/fixed_angle_roughness.py`. That
-workflow reruns the same fixed-angle laminar sweep for `sigma=0.0`, `0.5`,
-`1.0`, and `2.0 nm`, enables live plotting during each run, and then writes a
-combined first-order comparison figure. The current roughness implementation is
-a per-case scalar Debye-Waller damping model, so the example is intended to
-show how that maintained model changes the spectrum across energy.
+For a roughness-specific workflow, see
+`examples/simulation/fixed_angle_roughness/roughness_kind_comparison.py`.
+It compares the baseline, Debye-Waller, and random-interface models; see
+{doc}`roughness` for its configurable correlation and supercell studies.
 
 ```{image} images/simulation/fixed_angle_roughness_order1_comparison.png
-:alt: First-order fixed-angle roughness comparison for four Debye-Waller roughness levels
+:alt: First-order fixed-angle roughness comparison for the baseline, Debye-Waller, and random-interface models
 :align: center
 :width: 80%
 ```
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diff --git a/docs/tutorials/images/simulation/parameter_study_grid.png b/docs/tutorials/images/simulation/parameter_study_grid.png
index 8a04a2e..74b5857 100644
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diff --git a/docs/tutorials/images/simulation/solver_runtime_full.png b/docs/tutorials/images/simulation/solver_runtime_full.png
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diff --git a/docs/tutorials/index.md b/docs/tutorials/index.md
index 3b21e59..79345b6 100644
--- a/docs/tutorials/index.md
+++ b/docs/tutorials/index.md
@@ -10,6 +10,8 @@ execution.
 materials
 gratings
 simulations
+choosing-a-solver
+solver-difference-examples
 acceleration-backend
 optimizer
 ```
diff --git a/docs/tutorials/monochromator-sweep.md b/docs/tutorials/monochromator-sweep.md
index dc36e86..37e06f1 100644
--- a/docs/tutorials/monochromator-sweep.md
+++ b/docs/tutorials/monochromator-sweep.md
@@ -29,7 +29,7 @@ cases = grax.monochromator_cases(
 )
 
 runner = grax.BatchSimulationRunner(
-    default_fourier_orders=25,
+    fourier_orders=25,
     show_progress=True,
     live_plot=True,
     live_plot_x_key="energy_ev",
@@ -37,10 +37,10 @@ runner = grax.BatchSimulationRunner(
 )
 
 results = list(runner.run_cases(cases))
-grax.write_all_orders_csv(results, "examples/simulation/monochromator_sweep/results/monochromator_all_orders.csv")
+grax.write_all_orders_csv(results, "examples/simulation/monochromator_sweep/results/monochromator_all_orders_rcwa.csv")
 grax.plot_order_subset(
     results,
-    "examples/simulation/monochromator_sweep/results/monochromator_orders_1_3.png",
+    "examples/simulation/monochromator_sweep/results/monochromator_orders_1_3_rcwa.png",
     diffraction_orders=[1, 2, 3],
     title="Monochromator Sweep: Orders 1-3 Efficiency vs Energy",
 )
diff --git a/docs/tutorials/multilayer-theta-search.md b/docs/tutorials/multilayer-theta-search.md
index 25d10bf..17a654e 100644
--- a/docs/tutorials/multilayer-theta-search.md
+++ b/docs/tutorials/multilayer-theta-search.md
@@ -1,7 +1,7 @@
 # Multilayer theta search
 
 Use {func}`grax.run_multilayer_theta_search_sweep` when each energy point
-needs its own grazing-angle optimization before the final RCWA solve.
+needs its own grazing-angle optimization before the final selected-solver solve.
 
 The sweep internally performs, for each energy:
 
@@ -108,3 +108,11 @@ logger.info("Outputs written under: %s", output_dir)
 
 See `examples/simulation/multilayer_theta_search/multilayer_theta_search.py`
 for the full runnable script.
+
+## Polarization
+
+The search takes `polarization` (`s`/`TE` or `p`/`TM`, default `s`) and uses it
+for all three stages — rough scan, precise scan and final solve — so the selected
+angle and the reported efficiency come from the same polarization. Because the
+scan maximizes the selected order, `s` and `p` generally settle on slightly
+different angles.
diff --git a/docs/tutorials/multiprocessing.md b/docs/tutorials/multiprocessing.md
index e33b43a..0c98ed7 100644
--- a/docs/tutorials/multiprocessing.md
+++ b/docs/tutorials/multiprocessing.md
@@ -9,9 +9,9 @@ Serial execution:
 
 ```python
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=15,
-    default_polarization="p",
+    diffraction_order=1,
+    fourier_orders=15,
+    polarization="p",
     max_workers=1,
     show_progress=True,
 )
@@ -21,9 +21,9 @@ Automatic worker selection:
 
 ```python
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=15,
-    default_polarization="p",
+    diffraction_order=1,
+    fourier_orders=15,
+    polarization="p",
     max_workers="auto",
     show_progress=True,
 )
@@ -33,9 +33,9 @@ Explicit worker count:
 
 ```python
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=15,
-    default_polarization="p",
+    diffraction_order=1,
+    fourier_orders=15,
+    polarization="p",
     max_workers=8,
     show_progress=True,
 )
diff --git a/docs/tutorials/parameter-study.md b/docs/tutorials/parameter-study.md
index 91d13aa..0614ba3 100644
--- a/docs/tutorials/parameter-study.md
+++ b/docs/tutorials/parameter-study.md
@@ -33,7 +33,7 @@ study = grax.run_parameter_study(
 
 grax.plot_parameter_study(
     study,
-    output_filename="examples/simulation/parameter_study/results/parameter_study_grid.png",
+    output_filename="examples/simulation/parameter_study/results/parameter_study_grid_rcwa.png",
     title="Blazed Parameter Study: Orders vs Fourier/x/z Resolution",
 )
 ```
diff --git a/docs/tutorials/roughness.md b/docs/tutorials/roughness.md
index bf17dec..5fc307e 100644
--- a/docs/tutorials/roughness.md
+++ b/docs/tutorials/roughness.md
@@ -1,97 +1,76 @@
 # Roughness
 
-Use `examples/simulation/fixed_angle_roughness/fixed_angle_roughness.py` to
-compare Debye-Waller and random-interface roughness models across several
-roughness levels in a fixed-angle laminar sweep.
+GraxPy supports two roughness models that enter a simulation at different
+stages:
 
-This example reuses the fixed-angle simulation pattern, but reruns the same
-energy sweep for `debye-waller` and `random-interface` roughness at:
+- `debye-waller` preserves the discretized grating geometry and applies a
+  scalar Debye-Waller damping factor to the resulting efficiencies.
+- `random-interface` perturbs each material interface before textures are
+  built, so the solver sees the perturbed geometry directly.
 
-- `sigma=0.0 nm`
-- `sigma=0.5 nm`
-- `sigma=1.0 nm`
-- `sigma=2.0 nm`
-
-Roughness is selected when the grating is built:
+Configure either model on the grating:
 
 ```python
-roughness=grax.RoughnessSpec(kind="debye-waller", sigma_nm=0.5)
-roughness=grax.RoughnessSpec(kind="random-interface", sigma_nm=0.5, seed=0)
+roughness = grax.RoughnessSpec(kind="debye-waller", sigma_nm=1.0)
+roughness = grax.RoughnessSpec(
+    kind="random-interface",
+    sigma_nm=1.0,
+    seed=0,
+    correlation_length_nm=10.0,
+)
 ```
 
-During execution, each roughness sweep uses the batch runner with:
-
-- `live_plot=True`
-- `live_plot_x_key="energy_ev"`
-- `live_plot_order_count=1`
-- `max_workers="auto"`
-
-That means the first-order efficiency is plotted live while the cases are
-running, and the example also uses multiprocessing through the maintained batch
-execution path.
-
-After the runs finish, the workflow writes one all-orders CSV per roughness
-kind and level, plus a combined comparison plot for diffraction order `1`.
-
-## Explanation
+## Compare roughness models
 
-Grax supports two roughness implementations that enter the simulation at
-different stages.
+Run the maintained kind-comparison example:
 
-`debye-waller` roughness keeps the grating geometry unchanged. The RCWA solve
-uses the original discretized structure, and the solver then applies a
-Debye-Waller-style damping factor to the diffraction efficiencies. Use this mode
-when you want the existing scalar roughness correction:
-
-```python
-roughness=grax.RoughnessSpec(kind="debye-waller", sigma_nm=0.5)
+```bash
+python examples/simulation/fixed_angle_roughness/roughness_kind_comparison.py
 ```
 
-`random-interface` roughness changes the grating geometry before the RCWA
-textures are built. During texture generation, each material interface receives
-a deterministic random height modulation controlled by `seed`. Because the
-roughness is already represented in the geometry, Debye-Waller damping is not
-applied for this mode:
+By default it compares a no-roughness baseline, 1 nm Debye-Waller roughness,
+and 1 nm random-interface roughness. The random-interface case uses a
+10-supercell correlated field. It writes all-orders CSVs under
+`examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/`
+and comparison plots under
+`examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/`.
+Pass `--solver neviere` to run the same study with the Nevière path, or
+`--family` to run only one model family.
+
+```{figure} images/simulation/fixed_angle_roughness_order1_comparison.png
+:alt: First-order fixed-angle roughness comparison for the baseline, Debye-Waller, and random-interface models.
+:align: center
+:width: 80%
 
-```python
-roughness=grax.RoughnessSpec(kind="random-interface", sigma_nm=0.5, seed=0)
+The checked-in comparison plot shows the selected-order spectrum for the
+configured baseline and roughness-model cases.
 ```
 
-### Correlation length
+## Correlation length and supercells
 
-The random interface is a **Gaussian random field with a Gaussian
-autocorrelation**, `C(τ) = σ²·exp(−τ²/2ξ²)`, rather than uncorrelated white
-noise. The lateral autocorrelation length `ξ` is set by `correlation_length_nm`:
+Random-interface roughness is a Gaussian random field with Gaussian
+autocorrelation, `C(τ) = σ² exp(−τ² / 2ξ²)`. Use the correlation study to
+compare lateral correlation lengths and the effect of modelling several
+periods as one supercell:
 
-```python
-roughness=grax.RoughnessSpec(
-    kind="random-interface", sigma_nm=0.5, seed=0, correlation_length_nm=250.0
-)
+```bash
+python examples/simulation/fixed_angle_roughness/roughness_correlation.py
 ```
 
-- **`None` (default)** — the correlation length defaults to one tenth of the
-  grating period, which keeps a visible, physical per-period undulation at any
-  pitch.
-- **`0.0`** — reproduces the legacy uncorrelated (per-sample white-noise)
-  interface.
-- **`> 0`** — an explicit correlation length in nanometers.
+The default study compares the baseline and Debye-Waller cases with
+random-interface roughness at correlation lengths from 0 to 100 nm, both for
+one period and for a five-supercell field. Its outputs use the corresponding
+`results_roughness_correlation` and `plots_roughness_correlation` directories.
 
-Real metrology (e.g. an interferometer surface slice after Zernike removal)
-shows correlation lengths of order **~10 µm**. On fine-pitch gratings (period
-≈ 2.5 µm) such long correlations wash out geometrically — a roughness whose
-correlation length exceeds the grating period reduces to a near-constant height
-offset in single-period RCWA — so that long-scale regime is better represented
-by the `debye-waller` kind.
+Use `correlation_length_nm=None` to choose one tenth of the grating period,
+`0.0` for the legacy uncorrelated per-sample field, or a positive value in
+nanometers for an explicit correlation length.
 
 ## Per-layer roughness
 
-Both roughness models can be configured **per layer** instead of using a single
-grating-wide sigma. The value attached to a layer is the roughness of that
-layer's *top* interface; the substrate boundary and any layer without an
-explicit value fall back to the grating-level `RoughnessSpec.sigma_nm`. The
-`kind`, `seed`, and `resolution_factor` stay grating-global.
-
-For a `CustomStack`, set `roughness_sigma_nm` on each `LayerSpec`:
+Both models support per-layer interface roughness. For a `CustomStack`, set
+`roughness_sigma_nm` on each `LayerSpec`; layers without an explicit value use
+the grating-level sigma.
 
 ```python
 from grax.stacks import LayerSpec, assemble_custom_stack
@@ -110,30 +89,9 @@ grating = grax.LaminarGrating(
 )
 ```
 
-The built-in stacks expose equivalent per-layer arguments:
-`SingleLayerStack` accepts `layer_roughness_sigma_nm` /
-`top_cap_roughness_sigma_nm`, and `MultilayerStack` accepts
-`material_a_roughness_sigma_nm`, `material_b_roughness_sigma_nm`, and
-`top_cap_roughness_sigma_nm`.
-
-For `random-interface`, each interface is perturbed by its own sigma. For
-`debye-waller`, uncorrelated interfaces add in quadrature, so the per-layer
-sigmas reduce to an effective scalar
-`sigma_eff = sqrt(sum(sigma_i**2))` before damping is applied.
-
-The example plot below compares the no-roughness baseline with both roughness
-implementations at the configured sigma values.
-
-```{image} images/simulation/fixed_angle_roughness_order1_comparison.png
-:alt: First-order fixed-angle roughness comparison for Debye-Waller and random-interface roughness
-:align: center
-:width: 80%
-```
-
-See these files for the complete workflow:
-
-- `examples/simulation/fixed_angle_roughness/fixed_angle_roughness.py`
-- `examples/simulation/fixed_angle_roughness/comparison_fixed_angle_roughness.py`
+For `random-interface`, each interface receives its own perturbation. For
+`debye-waller`, uncorrelated per-interface sigmas combine in quadrature before
+the scalar damping is applied.
 
-For the baseline fixed-angle workflow without the roughness sweep wrapper, see
+For the baseline fixed-angle workflow without roughness, see
 {doc}`fixed-angle-sweep`.
diff --git a/docs/tutorials/simulations.md b/docs/tutorials/simulations.md
index 7c36081..22057b6 100644
--- a/docs/tutorials/simulations.md
+++ b/docs/tutorials/simulations.md
@@ -6,9 +6,9 @@ All simulation entrypoints let you set `polarization` explicitly. The accepted
 values are `s` and `p`; the maintained runnable examples in this section set
 `polarization="p"` on purpose rather than relying on defaults.
 
-If you want to see how the current Debye-Waller roughness model changes a
-fixed-angle spectrum, see
-`examples/simulation/fixed_angle_roughness/fixed_angle_roughness.py`.
+For fixed-angle roughness studies, use
+`examples/simulation/fixed_angle_roughness/roughness_kind_comparison.py` or
+`examples/simulation/fixed_angle_roughness/roughness_correlation.py`.
 
 ```{toctree}
 :maxdepth: 1
diff --git a/docs/tutorials/single-simulation.md b/docs/tutorials/single-simulation.md
index a25055c..b5794be 100644
--- a/docs/tutorials/single-simulation.md
+++ b/docs/tutorials/single-simulation.md
@@ -43,7 +43,13 @@ all_efficiencies = result.efficiency_all
 ```
 
 This maintained example sets `polarization="p"` explicitly so the script does
-not rely on the library default. Accepted values are `s` and `p`.
+not rely on the library default.
+
+Accepted values are `s` and `p`, plus the aliases `TE` and `TM` — `s` is TE and
+`p` is TM. The alias is resolved on the way in, so a result always reports the
+canonical `s` or `p` whichever spelling you passed. The two names coincide
+because this solver is one-dimensional and classical; see
+{func}`grax.normalize_polarization` for why that qualifier matters.
 
 To save a profile plot before or after running the simulation:
 
@@ -54,7 +60,7 @@ grating.plot_profile("examples/simulation/single_simulation/results/single_simul
 Export helpers accept the typed single result directly:
 
 ```python
-grax.write_all_orders_csv(result, "examples/simulation/single_simulation/results/single_simulation.csv")
+grax.write_all_orders_csv(result, "examples/simulation/single_simulation/results/single_simulation_rcwa.csv")
 ```
 
 See `examples/simulation/single_simulation/single_simulation.py` for the complete script.
diff --git a/docs/tutorials/solver-difference-examples.md b/docs/tutorials/solver-difference-examples.md
new file mode 100644
index 0000000..8e5c05a
--- /dev/null
+++ b/docs/tutorials/solver-difference-examples.md
@@ -0,0 +1,84 @@
+# Where the two solvers differ
+
+GraxPy's modal RCWA and Nevière differential-method paths solve the same
+one-dimensional grating problem through different layer-propagation methods.
+The general comparison example sweeps energy for a representative grating and
+compares the selected diffraction-order efficiency from both paths.
+
+```bash
+python examples/simulation/neviere_solver/neviere_solver.py
+```
+
+The example writes the comparison plot and one CSV per solver to
+`examples/simulation/neviere_solver/results/`.
+
+```{figure} images/simulation/neviere_solver_comparison.png
+:alt: Energy sweep comparing RCWA and Nevière diffraction efficiencies, with their absolute difference below.
+:width: 100%
+
+The upper panel compares the selected-order efficiencies from RCWA and
+Nevière across the energy sweep. The lower panel shows their absolute
+difference.
+```
+
+The examples below show three situations in which the solver choice changes
+what can be represented, how the profile is sampled, or the cost of a solve.
+For general solver-selection guidance, see {doc}`choosing-a-solver`.
+
+## Deep-grating range
+
+```bash
+python examples/simulation/deep_grating_limits/deep_grating_limits.py
+```
+
+This RETICOLO reference geometry sweeps a high-contrast lamellar grating from
+a fraction of a wavelength to deep profiles. The modal RCWA calculation can
+overflow when evanescent orders make its whole-layer propagation ill
+conditioned; the differential method propagates bounded sub-blocks and
+cascades their interface responses.
+
+```{figure} images/simulation/deep_grating_limits_p.png
+:alt: Zeroth-order transmission and energy-balance error as a deep grating is solved by RCWA and Nevière.
+:width: 100%
+
+The upper panel marks where the modal calculation stops. The lower panel shows
+the energy-balance error for the available results.
+```
+
+## Staircase and continuous sampling
+
+```bash
+python examples/simulation/continuous_vs_staircase/continuous_vs_staircase.py
+```
+
+Both solvers use the same z-sliced texture by default. With
+`NeviereOptions(z_sampling="continuous")`, the differential method instead
+re-expands the profile along z, removing the shared staircase approximation.
+
+```{figure} images/simulation/continuous_vs_staircase_p.png
+:alt: Staircase-convergence study comparing RCWA, Nevière texture sampling, and Nevière continuous sampling.
+:width: 100%
+
+The upper panel compares selected-order efficiencies as the z resolution is
+refined. The lower panel measures each staircase result against the continuous
+calculation.
+```
+
+## Runtime
+
+```bash
+python examples/simulation/solver_runtime/solver_runtime.py
+```
+
+The default command records reduced-resolution timings; add `--full` to
+reproduce the checked-in production-resolution comparison. Each timing is
+reported with the maximum all-order efficiency difference, so runtime can be
+read alongside agreement between the two paths.
+
+```{figure} images/simulation/solver_runtime_full.png
+:alt: Production-resolution runtime comparison of RCWA and Nevière for three representative gratings.
+:width: 100%
+
+The bars show seconds per energy point for the checked-in production-resolution
+benchmark cases.
+```
diff --git a/docs/tutorials/user-defined-cases.md b/docs/tutorials/user-defined-cases.md
index a1a485d..508eab6 100644
--- a/docs/tutorials/user-defined-cases.md
+++ b/docs/tutorials/user-defined-cases.md
@@ -51,8 +51,8 @@ for depth_nm in depths_nm:
     )
 
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=diffraction_order,
-    default_fourier_orders=25,
+    diffraction_order=diffraction_order,
+    fourier_orders=25,
     show_progress=True,
     on_error="continue",
 )
diff --git a/docs/validation/blazed-multilayer.md b/docs/validation/blazed-multilayer.md
index def6f82..245a828 100644
--- a/docs/validation/blazed-multilayer.md
+++ b/docs/validation/blazed-multilayer.md
@@ -41,7 +41,7 @@ The three curves in the comparison figure are obtained as follows:
 - `DiffraMod`: reference efficiencies from
   `validation/blazed_multilayer/simulation/DiffractMod_CrC_d4.8_N60.dat`
 - `grax energy-angle`: the grax sweep in
-  `validation/blazed_multilayer/blazed_multilayer_sweep.py`, where
+  `validation/blazed_multilayer/run_rcwa.py`, where
   each grax simulation uses the energy and grazing angle pair taken directly
   from the DiffraMod table
 - `grax theta-search`: the adaptive multilayer theta-search workflow, where
diff --git a/docs/validation/images/blazed_comparison_monochromator_orders_1_3_solver_comparison.png b/docs/validation/images/blazed_comparison_monochromator_orders_1_3_solver_comparison.png
new file mode 100644
index 0000000..bcb7449
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diff --git a/docs/validation/images/blazed_multilayer_all_orders_solver_comparison.png b/docs/validation/images/blazed_multilayer_all_orders_solver_comparison.png
new file mode 100644
index 0000000..e730ed0
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diff --git a/docs/validation/images/comparison_blazed_monochromator_sweep.png b/docs/validation/images/comparison_blazed_monochromator_sweep.png
index 86c2118..e184ce9 100644
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diff --git a/docs/validation/images/comparison_blazed_multilayer_grating_angle.png b/docs/validation/images/comparison_blazed_multilayer_grating_angle.png
index b715f8e..bf85252 100644
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diff --git a/docs/validation/images/comparison_blazed_multilayer_sweep.png b/docs/validation/images/comparison_blazed_multilayer_sweep.png
index 56844f6..5f36849 100644
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diff --git a/docs/validation/images/comparison_blazed_multilayer_sweep_550_600eV.png b/docs/validation/images/comparison_blazed_multilayer_sweep_550_600eV.png
index 6811173..9151a64 100644
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diff --git a/docs/validation/images/comparison_laminar_150lmm_monochromator.png b/docs/validation/images/comparison_laminar_150lmm_monochromator.png
index 5aa7b11..d504184 100644
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diff --git a/docs/validation/images/comparison_laminar_fixed_angle.png b/docs/validation/images/comparison_laminar_fixed_angle.png
index ba252c8..ae1f68e 100644
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diff --git a/docs/validation/images/laminar_150lmm_monochromator_all_orders_solver_comparison.png b/docs/validation/images/laminar_150lmm_monochromator_all_orders_solver_comparison.png
new file mode 100644
index 0000000..9395769
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diff --git a/docs/validation/images/laminar_fixed_angle_all_orders_solver_comparison.png b/docs/validation/images/laminar_fixed_angle_all_orders_solver_comparison.png
new file mode 100644
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diff --git a/docs/validation/index.md b/docs/validation/index.md
index 48745a2..b314331 100644
--- a/docs/validation/index.md
+++ b/docs/validation/index.md
@@ -8,6 +8,11 @@ This section compares `grax` with three external references:
 
 All simulation curves use the same optical constants, and measured data is included for comparison.
 
+`grax` also ships two selectable solver paths of its own, and
+[RCWA vs Nevière differential method](solver-comparison.md) runs the same
+validation cases through both. Note that REFLEC, one of the external references
+above, is itself a differential-method code.
+
 ```{toctree}
 :maxdepth: 1
 
@@ -15,4 +20,5 @@ blazed
 blazed-multilayer
 laminar
 laminar-150lmm
+solver-comparison
 ```
diff --git a/docs/validation/solver-comparison.md b/docs/validation/solver-comparison.md
new file mode 100644
index 0000000..2d29cf4
--- /dev/null
+++ b/docs/validation/solver-comparison.md
@@ -0,0 +1,144 @@
+# RCWA vs Nevière differential method
+
+The other pages in this section compare `grax` against external codes. This one
+compares `grax` against itself: the same validation sweeps run through both of
+its solvers.
+
+The two solvers share their inputs, their Fourier-space operators (including the
+Li/fast-Fourier-factorization rules for TM) and their efficiency extraction, and
+differ only in how they propagate through a layer — RCWA eigen-decomposes it,
+the differential method integrates it with fourth-order Runge–Kutta. They are
+therefore two numerical treatments of one truncated system, and any difference
+between them is integration error rather than a modelling difference.
+
+## Reproducing
+
+Each validation case has a `grating_definition.py` holding the grating and the
+sweep grid, and one runner per solver that imports it:
+
+```bash
+python validation/laminar/run_rcwa.py
+python validation/laminar/run_neviere.py
+python validation/laminar/comparison.py
+```
+
+Both runners read the same definition, so they cannot drift apart in geometry,
+energy grid or truncation. They write `*_rcwa.csv` and `*_neviere.csv` side by
+side, and `comparison.py` overlays both against the external reference codes.
+
+Both sides must come from the same revision; the last section on this page
+explains why the checked-in RCWA artifacts are not usable as one side. The
+per-order deviation figures quoted below come from a developer cross-check tool
+under `tools/`, which is not part of the validation workflow.
+
+## Results
+
+Maximum absolute deviation between the two solvers over every energy of each
+sweep, for reflected orders 1 to 3. `max/peak` normalizes that by the peak
+efficiency of the order, so it reads as a relative figure.
+
+| case | points | order | peak efficiency | max abs | RMS | max/peak |
+| --- | ---: | ---: | ---: | ---: | ---: | ---: |
+| laminar 400 l/mm | 601 | 1 | 0.179 | 5.6e-11 | 9.0e-12 | 3.1e-10 |
+|  |  | 2 | 0.021 | 1.2e-11 | 2.3e-12 | 5.6e-10 |
+|  |  | 3 | 0.009 | 6.2e-12 | 1.3e-12 | 6.9e-10 |
+| blazed 600 l/mm | 195 | 1 | 0.254 | 4.2e-12 | 1.6e-12 | 1.7e-11 |
+|  |  | 2 | 0.138 | 2.2e-12 | 9.5e-13 | 1.6e-11 |
+|  |  | 3 | 0.029 | 2.3e-12 | 1.2e-12 | 8.1e-11 |
+| laminar 150 l/mm | 496 | 1 | 0.331 | 3.9e-12 | 1.6e-12 | 1.2e-11 |
+|  |  | 2 | 0.116 | 2.9e-12 | 1.4e-12 | 2.5e-11 |
+|  |  | 3 | 0.042 | 1.4e-12 | 6.7e-13 | 3.4e-11 |
+| blazed 2400 l/mm multilayer | 173 | 1 | 0.007 | 2.3e-12 | 4.5e-13 | 3.2e-10 |
+|  |  | 2 | 0.675 | 8.7e-11 | 1.8e-11 | 1.3e-10 |
+|  |  | 3 | 0.002 | 1.2e-12 | 2.6e-13 | 5.8e-10 |
+
+All four cases run p polarization at the resolution and Fourier truncation each
+sweep normally uses. The `blazed_multilayer` case was run at `--stride 10`, which
+samples 173 of the 1727 reference energy-angle pairs across the full 500 to
+6000 eV range; the others use their full energy grids.
+
+The largest residual, on the laminar 400 l/mm case, is simply the case that
+accumulates the most Runge-Kutta error: it runs the most Fourier orders (30)
+across the most layers (310 slices at `z_resolution_nm = 0.1`).
+
+The differences are at the level of floating-point noise, not of physics. In the
+difference panel of each figure they appear as a jagged band with no structure
+tracking the efficiency curve, which is what accumulated Runge–Kutta truncation
+error looks like; a modelling difference would instead show up correlated with
+the spectral features.
+
+Tightening `NeviereOptions.step_phase` drives the residual down as its fourth
+power, confirming the same thing from the other direction. This is asserted in
+`tests/unit/test_neviere.py::test_neviere_converges_to_rcwa_as_step_phase_shrinks`.
+
+### Why the agreement is this close
+
+The brief for this work anticipated agreement "within a few percent". It is far
+better than that because the two solvers are not independent models of the
+grating — they are independent *propagators* for one shared model. They build
+the same Fourier operators through the same `layer_field_operators()`, see the
+same z-sliced permittivity, and extract efficiencies through the same
+`solve_stack_from_layer_blocks()`. The only thing that differs is how one layer
+is crossed, so the only thing that can differ in the answer is integration
+error.
+
+That makes the comparison a sharp test of the propagation and a weak test of
+everything upstream of it. Errors in the shared geometry, Fourier coefficients or
+flux normalization would move both solvers together and stay invisible here. The
+checks that do bite on the shared parts are the analytic Fresnel and
+energy-conservation tests in `tests/unit/test_neviere.py`, the published RETICOLO
+values in `tests/smoke/test_neviere_solver.py`, and the external-code comparisons
+on the other pages of this section.
+
+## Where the two would be expected to diverge
+
+Nothing in these cases stresses either solver, but the places to watch are:
+
+- **Deep gratings.** The modal solver evaluates `q / sinh(q d)` across a whole
+  layer and overflows above roughly seven wavelengths of depth for a
+  high-contrast profile. The differential method caps the optical thickness of
+  any transfer matrix it forms and remains stable far beyond that. None of the
+  X-ray validation gratings are anywhere near this limit; the effect is covered
+  by `tests/smoke/test_neviere_solver.py`.
+- **Metallic TM.** p-polarization at high permittivity contrast is where the
+  factorization rules matter most. Both solvers use the same rules, so they
+  converge together in the truncation order rather than against each other. All
+  four validation cases run p-polarization.
+- **High-contrast lamellar profiles.** For a genuinely lamellar grating the
+  staircase is exact, so the modal solver's layer treatment is exact and the
+  differential method's is a numerical approximation of it. The residual is
+  bounded by `step_phase` and is visible in the difference panel as a floor
+  rather than as structure.
+- **Continuous versus staircase sampling.** With
+  `NeviereOptions(z_sampling="continuous")` the differential method reads the
+  true profile instead of the shared staircase, so it will *not* match RCWA at a
+  coarse `z_resolution_nm` — it matches a much finer one. The comparisons above
+  use the default `"textures"` sampling so both solvers see identical geometry.
+
+## A note on the checked-in artifacts
+
+The RCWA CSVs committed under each `results/` directory predate several changes
+to the solver and its inputs, so they no longer reproduce from the current code.
+The comparison above therefore uses a fresh RCWA run (`run_rcwa.py`, written to
+`*_rcwa.csv`) rather than the committed files. The drift between the two is:
+
+| case | order 1 max drift | order 1 relative |
+| --- | ---: | ---: |
+| laminar 400 l/mm | 7.5e-3 | 4.1% |
+| blazed 600 l/mm | 6.2e-3 | 2.4% |
+| laminar 150 l/mm | 7.9e-2 | 22% |
+| blazed 2400 l/mm multilayer | 3.1e-4 | 4.5% |
+
+The laminar 150 l/mm figure is not representative of that curve: the drift is
+concentrated in the 12 to 28 eV tail, where the wavelength approaches the
+structure size. Its median drift over the sweep is 2.6e-4, and only 8.3% of
+points exceed 1e-2.
+
+This is independent of the differential method. The current RCWA solver and the
+current differential-method solver agree with each other to the table above;
+both differ from the older artifacts in the same way and by the same amount. For
+scale, on the laminar 400 l/mm case the RMS difference between the current
+solvers and the external references is 0.0024 (DiffractMod), 0.0036 (REFLEC) and
+0.0090 (RETICOLO), so this drift sits inside the spread between established
+codes — but it does mean the committed artifacts should be refreshed before
+they are used as a baseline for anything.
diff --git a/examples/grating/blazed_no_top_cap.py b/examples/grating/blazed_no_top_cap.py
index 295ab4e..a1e56b0 100644
--- a/examples/grating/blazed_no_top_cap.py
+++ b/examples/grating/blazed_no_top_cap.py
@@ -13,7 +13,7 @@
     layer_thickness_nm=28.77,
     top_cap_material=None,
     top_cap_thickness_nm=0.0,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
     x_resolution_nm=1.0,
     blaze_angle_deg=0.9,
     anti_blaze_angle_deg=None,
diff --git a/examples/grating/blazed_with_top_cap.py b/examples/grating/blazed_with_top_cap.py
index 03c3bb2..3ff1ae1 100644
--- a/examples/grating/blazed_with_top_cap.py
+++ b/examples/grating/blazed_with_top_cap.py
@@ -13,7 +13,7 @@
     layer_thickness_nm=28.77,
     top_cap_material="C",
     top_cap_thickness_nm=2.0,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
     x_resolution_nm=1.0,
     blaze_angle_deg=0.9,
     anti_blaze_angle_deg=None,
diff --git a/examples/grating/laminar_no_top_cap.py b/examples/grating/laminar_no_top_cap.py
index 50278f5..b3f1b4d 100644
--- a/examples/grating/laminar_no_top_cap.py
+++ b/examples/grating/laminar_no_top_cap.py
@@ -15,7 +15,7 @@
     layer_thickness_nm=28.77,
     top_cap_material=None,
     top_cap_thickness_nm=0.0,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
     x_resolution_nm=1.0,
     left_wall_angle_deg=15.0,
     right_wall_angle_deg=15.0,
diff --git a/examples/grating/laminar_with_top_cap.py b/examples/grating/laminar_with_top_cap.py
index d2602d2..6a0a4d7 100644
--- a/examples/grating/laminar_with_top_cap.py
+++ b/examples/grating/laminar_with_top_cap.py
@@ -15,7 +15,7 @@
     layer_thickness_nm=28.77,
     top_cap_material="C",
     top_cap_thickness_nm=2.0,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
     x_resolution_nm=1.0,
     left_wall_angle_deg=15.0,
     right_wall_angle_deg=15.0,
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index 0777996..f552b7f 100644
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diff --git a/examples/grating/results/blazed_no_top_cap.png b/examples/grating/results/blazed_no_top_cap.png
index 3d5cc33..d86463a 100644
Binary files a/examples/grating/results/blazed_no_top_cap.png and b/examples/grating/results/blazed_no_top_cap.png differ
diff --git a/examples/grating/results/blazed_with_top_cap.png b/examples/grating/results/blazed_with_top_cap.png
index 4beeb48..0c37655 100644
Binary files a/examples/grating/results/blazed_with_top_cap.png and b/examples/grating/results/blazed_with_top_cap.png differ
diff --git a/examples/grating/results/laminar_no_top_cap.png b/examples/grating/results/laminar_no_top_cap.png
index b31eca5..de9dac3 100644
Binary files a/examples/grating/results/laminar_no_top_cap.png and b/examples/grating/results/laminar_no_top_cap.png differ
diff --git a/examples/grating/results/laminar_with_top_cap.png b/examples/grating/results/laminar_with_top_cap.png
index 61eda89..2734350 100644
Binary files a/examples/grating/results/laminar_with_top_cap.png and b/examples/grating/results/laminar_with_top_cap.png differ
diff --git a/examples/grating/results/sinusoidal_custom_profile.png b/examples/grating/results/sinusoidal_custom_profile.png
index 052c31a..36c1f80 100644
Binary files a/examples/grating/results/sinusoidal_custom_profile.png and b/examples/grating/results/sinusoidal_custom_profile.png differ
diff --git a/examples/grating/run_all.sh b/examples/grating/run_all.sh
index d6313ca..3bb014a 100755
--- a/examples/grating/run_all.sh
+++ b/examples/grating/run_all.sh
@@ -1,13 +1,15 @@
-#!/bin/bash
+#!/usr/bin/env bash
 # Run all grating profile generation scripts
+set -euo pipefail
 
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+PYTHON_BIN="${PYTHON_BIN:-python}"
 
-python "$SCRIPT_DIR/laminar_no_top_cap.py" "$@"
-python "$SCRIPT_DIR/laminar_with_top_cap.py" "$@"
-python "$SCRIPT_DIR/blazed_no_top_cap.py" "$@"
-python "$SCRIPT_DIR/blazed_with_top_cap.py" "$@"
-python "$SCRIPT_DIR/blazed_multilayer_custom_stack.py" "$@"
-python "$SCRIPT_DIR/sinusoidal_custom_profile.py" "$@"
-python "$SCRIPT_DIR/afm_preprocessing_blazed_profile.py" "$@"
-python "$SCRIPT_DIR/afm_preprocessing_laminar_profile.py" "$@"
+"${PYTHON_BIN}" "$SCRIPT_DIR/laminar_no_top_cap.py" "$@"
+"${PYTHON_BIN}" "$SCRIPT_DIR/laminar_with_top_cap.py" "$@"
+"${PYTHON_BIN}" "$SCRIPT_DIR/blazed_no_top_cap.py" "$@"
+"${PYTHON_BIN}" "$SCRIPT_DIR/blazed_with_top_cap.py" "$@"
+"${PYTHON_BIN}" "$SCRIPT_DIR/blazed_multilayer_custom_stack.py" "$@"
+"${PYTHON_BIN}" "$SCRIPT_DIR/sinusoidal_custom_profile.py" "$@"
+"${PYTHON_BIN}" "$SCRIPT_DIR/afm_preprocessing_blazed_profile.py" "$@"
+"${PYTHON_BIN}" "$SCRIPT_DIR/afm_preprocessing_laminar_profile.py" "$@"
diff --git a/examples/grating/sinusoidal_custom_profile.py b/examples/grating/sinusoidal_custom_profile.py
index 4661613..890c5cc 100644
--- a/examples/grating/sinusoidal_custom_profile.py
+++ b/examples/grating/sinusoidal_custom_profile.py
@@ -43,7 +43,7 @@ def profile_depth_nm(self) -> float:
     top_cap_material=None,
     top_cap_thickness_nm=0.0,
     x_resolution_nm=1.0,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
 )
 
 parser = argparse.ArgumentParser(description="Generate custom sinusoidal grating profile plot")
diff --git a/examples/optimizer/optimizer_blazed/0_fit_blazed_grating.py b/examples/optimizer/optimizer_blazed/0_fit_blazed_grating.py
index de3ca3d..bdfb37a 100644
--- a/examples/optimizer/optimizer_blazed/0_fit_blazed_grating.py
+++ b/examples/optimizer/optimizer_blazed/0_fit_blazed_grating.py
@@ -99,43 +99,49 @@ def build_grating(parameters: dict[str, float]) -> BlazedGrating:
     "evaluation_energies_ev": list(evaluation_energies_ev),
 }
 
-try:
-    result = optimize_to_measurements(spec)
-except ImportError as error:
-    print(error)
-    print("Install the optional optimizer dependency first: `pip install .[opt]`.")
-    raise SystemExit(1) from error
-
-fitted_parameters_path = results_dir / "fitted_parameters.json"
-payload = json.loads(result.result_json_path.read_text(encoding="utf-8"))
-payload["result_json_path"] = str(result.result_json_path)
-payload["trial_history_csv_path"] = str(result.trial_history_csv_path)
-payload["best_fit_plot_path"] = (
-    None if result.best_fit_plot_path is None else str(result.best_fit_plot_path)
-)
-payload["loss_history_plot_path"] = (
-    None if result.loss_history_plot_path is None else str(result.loss_history_plot_path)
-)
-fitted_parameters_path.write_text(json.dumps(payload, indent=2), encoding="utf-8")
-
-print(f"Measurement: {result.measurement_path}")
-print(f"Optimizer backend request: {optimizer_backend}")
-print(f"Optimizer max_workers request: {optimizer_max_workers}")
-print(
-    f"Baseline top-cap setting: use_top_cap={use_top_cap}, "
-    f"material={top_cap_material_name if use_top_cap else 'None'}, "
-    f"thickness_nm={top_cap_thickness_nm}"
-)
-print(f"Best loss: {result.best_loss:.6g}")
-print(f"Best parameters: {result.best_parameters}")
-print(f"Completed trials: {result.completed_trials}")
-print(f"Stopped early: {result.stopped_early}")
-if result.early_stop_reason is not None:
-    print(f"Early-stop reason: {result.early_stop_reason}")
-print(f"Fitted parameters JSON: {fitted_parameters_path}")
-print(f"Best result JSON: {result.result_json_path}")
-print(f"Trial history CSV: {result.trial_history_csv_path}")
-if result.best_fit_plot_path is not None:
-    print(f"Best-fit plot: {result.best_fit_plot_path}")
-if result.loss_history_plot_path is not None:
-    print(f"Loss-history plot: {result.loss_history_plot_path}")
+
+def main() -> None:
+    try:
+        result = optimize_to_measurements(spec)
+    except ImportError as error:
+        print(error)
+        print("Install the optional optimizer dependency first: `pip install .[opt]`.")
+        raise SystemExit(1) from error
+
+    fitted_parameters_path = results_dir / "fitted_parameters.json"
+    payload = json.loads(result.result_json_path.read_text(encoding="utf-8"))
+    payload["result_json_path"] = str(result.result_json_path)
+    payload["trial_history_csv_path"] = str(result.trial_history_csv_path)
+    payload["best_fit_plot_path"] = (
+        None if result.best_fit_plot_path is None else str(result.best_fit_plot_path)
+    )
+    payload["loss_history_plot_path"] = (
+        None if result.loss_history_plot_path is None else str(result.loss_history_plot_path)
+    )
+    fitted_parameters_path.write_text(json.dumps(payload, indent=2), encoding="utf-8")
+
+    print(f"Measurement: {result.measurement_path}")
+    print(f"Optimizer backend request: {optimizer_backend}")
+    print(f"Optimizer max_workers request: {optimizer_max_workers}")
+    print(
+        f"Baseline top-cap setting: use_top_cap={use_top_cap}, "
+        f"material={top_cap_material_name if use_top_cap else 'None'}, "
+        f"thickness_nm={top_cap_thickness_nm}"
+    )
+    print(f"Best loss: {result.best_loss:.6g}")
+    print(f"Best parameters: {result.best_parameters}")
+    print(f"Completed trials: {result.completed_trials}")
+    print(f"Stopped early: {result.stopped_early}")
+    if result.early_stop_reason is not None:
+        print(f"Early-stop reason: {result.early_stop_reason}")
+    print(f"Fitted parameters JSON: {fitted_parameters_path}")
+    print(f"Best result JSON: {result.result_json_path}")
+    print(f"Trial history CSV: {result.trial_history_csv_path}")
+    if result.best_fit_plot_path is not None:
+        print(f"Best-fit plot: {result.best_fit_plot_path}")
+    if result.loss_history_plot_path is not None:
+        print(f"Loss-history plot: {result.loss_history_plot_path}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/optimizer/optimizer_blazed/1_run_simulation_design_parameters.py b/examples/optimizer/optimizer_blazed/1_run_simulation_design_parameters.py
index 3567e0f..6384733 100644
--- a/examples/optimizer/optimizer_blazed/1_run_simulation_design_parameters.py
+++ b/examples/optimizer/optimizer_blazed/1_run_simulation_design_parameters.py
@@ -26,70 +26,77 @@
     z_resolution_nm,
 )
 
-results_dir.mkdir(parents=True, exist_ok=True)
 
-silicon = pd.read_csv(optical_constants_dir / "OC_Si_SSTR.dat", sep=r"\s*,\s*|\s+", engine="python")
-silicon.attrs["name"] = "Si"
-gold = pd.read_csv(optical_constants_dir / "OC_Au_SSTR.dat", sep=r"\s*,\s*|\s+", engine="python")
-gold.attrs["name"] = "Au"
-carbon = pd.read_csv(
-    optical_constants_dir / "n_C_cxro.txt",
-    skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-carbon.attrs["name"] = "C"
-top_cap_material = carbon if use_top_cap else None
+def main() -> None:
 
-measurement = pd.read_csv(
-    measurement_path,
-    sep=r"\s+",
-    header=None,
-    names=["energy_ev", "efficiency"],
-).apply(pd.to_numeric, errors="coerce").dropna()
-energies = np.asarray(measurement["energy_ev"], dtype=float)
+    results_dir.mkdir(parents=True, exist_ok=True)
 
-design_grating = grax.BlazedGrating(
-    period_lpermm=period_lpermm,
-    blaze_angle_deg=blaze_angle_deg,
-    anti_blaze_angle_deg=anti_blaze_angle_deg,
-    substrate_material=silicon,
-    layer_material=gold,
-    layer_thickness_nm=layer_thickness_nm,
-    top_cap_material=top_cap_material,
-    top_cap_thickness_nm=top_cap_thickness_nm,
-    z_resolution_nm=z_resolution_nm,
-    x_resolution_nm=x_resolution_nm,
-)
+    silicon = pd.read_csv(optical_constants_dir / "OC_Si_SSTR.dat", sep=r"\s*,\s*|\s+", engine="python")
+    silicon.attrs["name"] = "Si"
+    gold = pd.read_csv(optical_constants_dir / "OC_Au_SSTR.dat", sep=r"\s*,\s*|\s+", engine="python")
+    gold.attrs["name"] = "Au"
+    carbon = pd.read_csv(
+        optical_constants_dir / "n_C_cxro.txt",
+        skiprows=1,
+        sep=r"\s*,\s*|\s+",
+        engine="python",
+    )
+    carbon.attrs["name"] = "C"
+    top_cap_material = carbon if use_top_cap else None
 
-cases = grax.monochromator_cases(
-    grating=design_grating,
-    energies_ev=energies,
-    period_lpermm=period_lpermm,
-    diffraction_order=diffraction_order,
-    cff=cff,
-    polarization="p",
-)
+    measurement = pd.read_csv(
+        measurement_path,
+        sep=r"\s+",
+        header=None,
+        names=["energy_ev", "efficiency"],
+    ).apply(pd.to_numeric, errors="coerce").dropna()
+    energies = np.asarray(measurement["energy_ev"], dtype=float)
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=diffraction_order,
-    default_fourier_orders=fourier_orders,
-    max_workers="auto",
-    show_progress=True,
-    live_plot=False,
-    on_error="fail_fast",
-    backend="numba",
-)
-results = list(runner.run_cases(cases))
+    design_grating = grax.BlazedGrating(
+        period_lpermm=period_lpermm,
+        blaze_angle_deg=blaze_angle_deg,
+        anti_blaze_angle_deg=anti_blaze_angle_deg,
+        substrate_material=silicon,
+        layer_material=gold,
+        layer_thickness_nm=layer_thickness_nm,
+        top_cap_material=top_cap_material,
+        top_cap_thickness_nm=top_cap_thickness_nm,
+        z_resolution_nm=z_resolution_nm,
+        x_resolution_nm=x_resolution_nm,
+    )
 
-output_csv_path = results_dir / "simulated_curve_initial.csv"
-grax.write_all_orders_csv(results, output_csv_path)
-print(f"Initial-parameter simulation CSV: {output_csv_path}")
-print(
-    "Initial simulation settings: "
-    f"cff={cff}, fourier_orders={fourier_orders}, "
-    "simulation_backend=numba, "
-    f"x_resolution_nm={x_resolution_nm}, z_resolution_nm={z_resolution_nm}, "
-    f"top_cap_material={'C' if use_top_cap else 'None'}, "
-    f"top_cap_thickness_nm={top_cap_thickness_nm}"
-)
+    cases = grax.monochromator_cases(
+        grating=design_grating,
+        energies_ev=energies,
+        period_lpermm=period_lpermm,
+        diffraction_order=diffraction_order,
+        cff=cff,
+        polarization="p",
+    )
+
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=diffraction_order,
+        fourier_orders=fourier_orders,
+        max_workers="auto",
+        show_progress=True,
+        live_plot=True,
+        on_error="fail_fast",
+        backend="numba",
+    )
+    results = list(runner.run_cases(cases))
+
+    output_csv_path = results_dir / "simulated_curve_initial.csv"
+    grax.write_all_orders_csv(results, output_csv_path)
+    print(f"Initial-parameter simulation CSV: {output_csv_path}")
+    print(
+        "Initial simulation settings: "
+        f"cff={cff}, fourier_orders={fourier_orders}, "
+        "simulation_backend=numba, "
+        f"x_resolution_nm={x_resolution_nm}, z_resolution_nm={z_resolution_nm}, "
+        f"top_cap_material={'C' if use_top_cap else 'None'}, "
+        f"top_cap_thickness_nm={top_cap_thickness_nm}"
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/optimizer/optimizer_blazed/2_run_simulation_fitted_parameters.py b/examples/optimizer/optimizer_blazed/2_run_simulation_fitted_parameters.py
index 714ea64..270a567 100644
--- a/examples/optimizer/optimizer_blazed/2_run_simulation_fitted_parameters.py
+++ b/examples/optimizer/optimizer_blazed/2_run_simulation_fitted_parameters.py
@@ -26,84 +26,91 @@
     z_resolution_nm as baseline_z_resolution_nm,
 )
 
-results_dir.mkdir(parents=True, exist_ok=True)
 
-fitted_parameters_path = results_dir / "fitted_parameters.json"
-if not fitted_parameters_path.exists():
-    raise FileNotFoundError(
-        f"Missing fitted parameters file: {fitted_parameters_path}. Run 0_fit_blazed_grating.py first."
+def main() -> None:
+
+    results_dir.mkdir(parents=True, exist_ok=True)
+
+    fitted_parameters_path = results_dir / "fitted_parameters.json"
+    if not fitted_parameters_path.exists():
+        raise FileNotFoundError(
+            f"Missing fitted parameters file: {fitted_parameters_path}. Run 0_fit_blazed_grating.py first."
+        )
+
+    silicon = pd.read_csv(optical_constants_dir / "OC_Si_SSTR.dat", sep=r"\s*,\s*|\s+", engine="python")
+    silicon.attrs["name"] = "Si"
+    gold = pd.read_csv(optical_constants_dir / "OC_Au_SSTR.dat", sep=r"\s*,\s*|\s+", engine="python")
+    gold.attrs["name"] = "Au"
+    carbon = pd.read_csv(
+        optical_constants_dir / "n_C_cxro.txt",
+        skiprows=1,
+        sep=r"\s*,\s*|\s+",
+        engine="python",
     )
+    carbon.attrs["name"] = "C"
 
-silicon = pd.read_csv(optical_constants_dir / "OC_Si_SSTR.dat", sep=r"\s*,\s*|\s+", engine="python")
-silicon.attrs["name"] = "Si"
-gold = pd.read_csv(optical_constants_dir / "OC_Au_SSTR.dat", sep=r"\s*,\s*|\s+", engine="python")
-gold.attrs["name"] = "Au"
-carbon = pd.read_csv(
-    optical_constants_dir / "n_C_cxro.txt",
-    skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-carbon.attrs["name"] = "C"
+    measurement = pd.read_csv(
+        measurement_path,
+        sep=r"\s+",
+        header=None,
+        names=["energy_ev", "efficiency"],
+    ).apply(pd.to_numeric, errors="coerce").dropna()
+    energies = np.asarray(measurement["energy_ev"], dtype=float)
 
-measurement = pd.read_csv(
-    measurement_path,
-    sep=r"\s+",
-    header=None,
-    names=["energy_ev", "efficiency"],
-).apply(pd.to_numeric, errors="coerce").dropna()
-energies = np.asarray(measurement["energy_ev"], dtype=float)
-
-payload = json.loads(fitted_parameters_path.read_text(encoding="utf-8"))
-fitted_grating_parameters = {
-    "period_lpermm": float(baseline_period_lpermm),
-    "blaze_angle_deg": float(baseline_blaze_angle_deg),
-    "anti_blaze_angle_deg": float(baseline_anti_blaze_angle_deg),
-    "layer_thickness_nm": float(baseline_layer_thickness_nm),
-    "top_cap_thickness_nm": float(baseline_top_cap_thickness_nm),
-    "x_resolution_nm": float(baseline_x_resolution_nm),
-    "z_resolution_nm": float(baseline_z_resolution_nm),
-}
-fitted_grating_parameters.update(dict(payload.get("best_grating_parameters", {})))
-fitted_grating_parameters["substrate_material"] = silicon
-fitted_grating_parameters["layer_material"] = gold
-fitted_grating_parameters["top_cap_material"] = carbon if use_top_cap else None
-fitted_grating = grax.BlazedGrating(**fitted_grating_parameters)
-
-cases = grax.monochromator_cases(
-    grating=fitted_grating,
-    energies_ev=energies,
-    period_lpermm=float(fitted_grating_parameters["period_lpermm"]),
-    diffraction_order=int(payload.get("diffraction_order", baseline_diffraction_order)),
-    cff=float(payload.get("cff", baseline_cff)),
-    polarization="p",
-)
+    payload = json.loads(fitted_parameters_path.read_text(encoding="utf-8"))
+    fitted_grating_parameters = {
+        "period_lpermm": float(baseline_period_lpermm),
+        "blaze_angle_deg": float(baseline_blaze_angle_deg),
+        "anti_blaze_angle_deg": float(baseline_anti_blaze_angle_deg),
+        "layer_thickness_nm": float(baseline_layer_thickness_nm),
+        "top_cap_thickness_nm": float(baseline_top_cap_thickness_nm),
+        "x_resolution_nm": float(baseline_x_resolution_nm),
+        "z_resolution_nm": float(baseline_z_resolution_nm),
+    }
+    fitted_grating_parameters.update(dict(payload.get("best_grating_parameters", {})))
+    fitted_grating_parameters["substrate_material"] = silicon
+    fitted_grating_parameters["layer_material"] = gold
+    fitted_grating_parameters["top_cap_material"] = carbon if use_top_cap else None
+    fitted_grating = grax.BlazedGrating(**fitted_grating_parameters)
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=int(payload.get("diffraction_order", baseline_diffraction_order)),
-    default_fourier_orders=int(payload.get("fourier_orders", baseline_fourier_orders)),
-    max_workers="auto",
-    show_progress=True,
-    live_plot=False,
-    on_error="fail_fast",
-    backend="numba",
-)
-results = list(runner.run_cases(cases))
-
-output_csv_path = results_dir / "simulated_curve_fitted.csv"
-grax.write_all_orders_csv(results, output_csv_path)
-print(f"Fitted-parameter simulation CSV: {output_csv_path}")
-print(
-    "Fitted simulation settings: "
-    f"cff={float(payload.get('cff', baseline_cff))}, "
-    f"fourier_orders={int(payload.get('fourier_orders', baseline_fourier_orders))}, "
-    "simulation_backend=numba, "
-    f"x_resolution_nm={fitted_grating.x_resolution_nm}, "
-    f"z_resolution_nm={fitted_grating.z_resolution_nm}, "
-    f"top_cap_material={'C' if use_top_cap else 'None'}, "
-    "top_cap_thickness_source=best_grating_parameters"
-)
-print(
-    "Baseline defaults (used only if payload fields are missing): "
-    f"x_resolution_nm={baseline_x_resolution_nm}, z_resolution_nm={baseline_z_resolution_nm}"
-)
+    cases = grax.monochromator_cases(
+        grating=fitted_grating,
+        energies_ev=energies,
+        period_lpermm=float(fitted_grating_parameters["period_lpermm"]),
+        diffraction_order=int(payload.get("diffraction_order", baseline_diffraction_order)),
+        cff=float(payload.get("cff", baseline_cff)),
+        polarization="p",
+    )
+
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=int(payload.get("diffraction_order", baseline_diffraction_order)),
+        fourier_orders=int(payload.get("fourier_orders", baseline_fourier_orders)),
+        max_workers="auto",
+        show_progress=True,
+        live_plot=True,
+        on_error="fail_fast",
+        backend="numba",
+    )
+    results = list(runner.run_cases(cases))
+
+    output_csv_path = results_dir / "simulated_curve_fitted.csv"
+    grax.write_all_orders_csv(results, output_csv_path)
+    print(f"Fitted-parameter simulation CSV: {output_csv_path}")
+    print(
+        "Fitted simulation settings: "
+        f"cff={float(payload.get('cff', baseline_cff))}, "
+        f"fourier_orders={int(payload.get('fourier_orders', baseline_fourier_orders))}, "
+        "simulation_backend=numba, "
+        f"x_resolution_nm={fitted_grating.x_resolution_nm}, "
+        f"z_resolution_nm={fitted_grating.z_resolution_nm}, "
+        f"top_cap_material={'C' if use_top_cap else 'None'}, "
+        "top_cap_thickness_source=best_grating_parameters"
+    )
+    print(
+        "Baseline defaults (used only if payload fields are missing): "
+        f"x_resolution_nm={baseline_x_resolution_nm}, z_resolution_nm={baseline_z_resolution_nm}"
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/optimizer/optimizer_blazed/3_plot_blazed_fit_comparison.py b/examples/optimizer/optimizer_blazed/3_plot_blazed_fit_comparison.py
index e8b80e7..0ce7ae7 100644
--- a/examples/optimizer/optimizer_blazed/3_plot_blazed_fit_comparison.py
+++ b/examples/optimizer/optimizer_blazed/3_plot_blazed_fit_comparison.py
@@ -8,45 +8,52 @@
 import pandas as pd
 from example_config import measurement_path, results_dir
 
-fitted_parameters_path = results_dir / "fitted_parameters.json"
-initial_csv_path = results_dir / "simulated_curve_initial.csv"
-fitted_csv_path = results_dir / "simulated_curve_fitted.csv"
-alternative_fitted_csv_path = results_dir / "simulated_curve_fitted_alternative.csv"
-comparison_plot_path = results_dir / "blazed_fit_measurement_comparison.png"
-
-measurement = pd.read_csv(
-    measurement_path,
-    sep=r"\s+",
-    header=None,
-    names=["energy_ev", "efficiency"],
-).apply(pd.to_numeric, errors="coerce").dropna()
-initial_frame = pd.read_csv(initial_csv_path)
-fitted_frame = pd.read_csv(fitted_csv_path)
-alternative_fitted_frame = (
-    pd.read_csv(alternative_fitted_csv_path) if alternative_fitted_csv_path.exists() else None
-)
-fitted_parameters = json.loads(fitted_parameters_path.read_text(encoding="utf-8"))
-evaluation_energies_ev = [float(v) for v in fitted_parameters.get("evaluation_energies_ev", [])]
-
-initial_m1 = initial_frame[initial_frame["order"] == -1].sort_values("energy_ev")
-fitted_m1 = fitted_frame[fitted_frame["order"] == -1].sort_values("energy_ev")
-
-figure, axis = plt.subplots(figsize=(11, 7))
-axis.plot(measurement["energy_ev"], measurement["efficiency"], "o", label="Measurement", markersize=2.5)
-axis.plot(initial_m1["energy_ev"], initial_m1["efficiency"], "-", label="Initial design")
-axis.plot(fitted_m1["energy_ev"], fitted_m1["efficiency"], "-", label="Fitted")
-
-if evaluation_energies_ev:
-    y_min, y_max = axis.get_ylim()
-    axis.vlines(evaluation_energies_ev, y_min, y_max, colors="red", linestyles=":", linewidth=0.8, label="Optimization energies")
-    axis.set_ylim(y_min, y_max)
-axis.set_xlabel("Energy (eV)")
-axis.set_ylabel("Efficiency")
-axis.set_title("Blazed fit: measurement vs initial vs fitted")
-axis.grid(alpha=0.3)
-axis.legend(loc="best")
-figure.tight_layout()
-figure.savefig(comparison_plot_path, dpi=200, bbox_inches="tight")
-plt.close(figure)
-
-print(f"Comparison plot: {comparison_plot_path}")
+
+def main() -> None:
+
+    fitted_parameters_path = results_dir / "fitted_parameters.json"
+    initial_csv_path = results_dir / "simulated_curve_initial.csv"
+    fitted_csv_path = results_dir / "simulated_curve_fitted.csv"
+    alternative_fitted_csv_path = results_dir / "simulated_curve_fitted_alternative.csv"
+    comparison_plot_path = results_dir / "blazed_fit_measurement_comparison.png"
+
+    measurement = pd.read_csv(
+        measurement_path,
+        sep=r"\s+",
+        header=None,
+        names=["energy_ev", "efficiency"],
+    ).apply(pd.to_numeric, errors="coerce").dropna()
+    initial_frame = pd.read_csv(initial_csv_path)
+    fitted_frame = pd.read_csv(fitted_csv_path)
+    alternative_fitted_frame = (
+        pd.read_csv(alternative_fitted_csv_path) if alternative_fitted_csv_path.exists() else None
+    )
+    fitted_parameters = json.loads(fitted_parameters_path.read_text(encoding="utf-8"))
+    evaluation_energies_ev = [float(v) for v in fitted_parameters.get("evaluation_energies_ev", [])]
+
+    initial_m1 = initial_frame[initial_frame["order"] == -1].sort_values("energy_ev")
+    fitted_m1 = fitted_frame[fitted_frame["order"] == -1].sort_values("energy_ev")
+
+    figure, axis = plt.subplots(figsize=(11, 7))
+    axis.plot(measurement["energy_ev"], measurement["efficiency"], "o", label="Measurement", markersize=2.5)
+    axis.plot(initial_m1["energy_ev"], initial_m1["efficiency"], "-", label="Initial design")
+    axis.plot(fitted_m1["energy_ev"], fitted_m1["efficiency"], "-", label="Fitted")
+
+    if evaluation_energies_ev:
+        y_min, y_max = axis.get_ylim()
+        axis.vlines(evaluation_energies_ev, y_min, y_max, colors="red", linestyles=":", linewidth=0.8, label="Optimization energies")
+        axis.set_ylim(y_min, y_max)
+    axis.set_xlabel("Energy (eV)")
+    axis.set_ylabel("Efficiency")
+    axis.set_title("Blazed fit: measurement vs initial vs fitted")
+    axis.grid(alpha=0.3)
+    axis.legend(loc="best")
+    figure.tight_layout()
+    figure.savefig(comparison_plot_path, dpi=200, bbox_inches="tight")
+    plt.close(figure)
+
+    print(f"Comparison plot: {comparison_plot_path}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/optimizer/optimizer_blazed/results/blazed_fit/best_fit.png b/examples/optimizer/optimizer_blazed/results/blazed_fit/best_fit.png
index 0de87b0..182ef6b 100644
Binary files a/examples/optimizer/optimizer_blazed/results/blazed_fit/best_fit.png and b/examples/optimizer/optimizer_blazed/results/blazed_fit/best_fit.png differ
diff --git a/examples/optimizer/optimizer_blazed/results/blazed_fit/best_result.json b/examples/optimizer/optimizer_blazed/results/blazed_fit/best_result.json
index 29e2bee..3e94cde 100644
--- a/examples/optimizer/optimizer_blazed/results/blazed_fit/best_result.json
+++ b/examples/optimizer/optimizer_blazed/results/blazed_fit/best_result.json
@@ -2,7 +2,7 @@
   "optimization_mode": "measurement_fit",
   "experiment_name": "blazed_fit",
   "objective_name": "loss",
-  "measurement_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_blazed/GR600-BEIChem_energy-Cff2.5.dat",
+  "measurement_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_blazed/GR600-BEIChem_energy-Cff2.5.dat",
   "evaluation_mode": "energy_only",
   "evaluation_case_mode": "energy_only",
   "evaluation_energies_ev": [
@@ -72,14 +72,14 @@
     ]
   },
   "equality_constraints": {},
-  "best_loss": 3.422211971978115e-05,
+  "best_loss": 3.331287998447174e-05,
   "best_parameters": {
-    "blaze_angle_deg": 0.8594103033260448,
+    "blaze_angle_deg": 0.8641036454094532,
     "anti_blaze_angle_deg": 2.0,
     "top_cap_thickness_nm": 2.0
   },
   "best_grating_parameters": {
-    "blaze_angle_deg": 0.8594103033260448,
+    "blaze_angle_deg": 0.8641036454094532,
     "anti_blaze_angle_deg": 2.0,
     "top_cap_thickness_nm": 2.0
   },
@@ -91,6 +91,11 @@
   "early_stop_reason": null,
   "backend_requested": "auto",
   "backend_effective": "numba",
+  "solver": "rcwa",
+  "solver_options": null,
+  "optimizer_execution_strategy": "trial_batch_runner",
+  "optimizer_requested_max_workers": "auto",
+  "optimizer_resolved_max_workers": 8,
   "diffraction_order": 1,
   "fourier_orders": 10,
   "angle_mode": "cff",
diff --git a/examples/optimizer/optimizer_blazed/results/blazed_fit/blazed_fit_measurement_comparison.png b/examples/optimizer/optimizer_blazed/results/blazed_fit/blazed_fit_measurement_comparison.png
index ff29ba1..1f8cae3 100644
Binary files a/examples/optimizer/optimizer_blazed/results/blazed_fit/blazed_fit_measurement_comparison.png and b/examples/optimizer/optimizer_blazed/results/blazed_fit/blazed_fit_measurement_comparison.png differ
diff --git a/examples/optimizer/optimizer_blazed/results/blazed_fit/fitted_parameters.json b/examples/optimizer/optimizer_blazed/results/blazed_fit/fitted_parameters.json
index 3bcc533..e6ca2d6 100644
--- a/examples/optimizer/optimizer_blazed/results/blazed_fit/fitted_parameters.json
+++ b/examples/optimizer/optimizer_blazed/results/blazed_fit/fitted_parameters.json
@@ -2,7 +2,7 @@
   "optimization_mode": "measurement_fit",
   "experiment_name": "blazed_fit",
   "objective_name": "loss",
-  "measurement_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_blazed/GR600-BEIChem_energy-Cff2.5.dat",
+  "measurement_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_blazed/GR600-BEIChem_energy-Cff2.5.dat",
   "evaluation_mode": "energy_only",
   "evaluation_case_mode": "energy_only",
   "evaluation_energies_ev": [
@@ -72,14 +72,14 @@
     ]
   },
   "equality_constraints": {},
-  "best_loss": 3.422211971978115e-05,
+  "best_loss": 3.331287998447174e-05,
   "best_parameters": {
-    "blaze_angle_deg": 0.8594103033260448,
+    "blaze_angle_deg": 0.8641036454094532,
     "anti_blaze_angle_deg": 2.0,
     "top_cap_thickness_nm": 2.0
   },
   "best_grating_parameters": {
-    "blaze_angle_deg": 0.8594103033260448,
+    "blaze_angle_deg": 0.8641036454094532,
     "anti_blaze_angle_deg": 2.0,
     "top_cap_thickness_nm": 2.0
   },
@@ -91,12 +91,17 @@
   "early_stop_reason": null,
   "backend_requested": "auto",
   "backend_effective": "numba",
+  "solver": "rcwa",
+  "solver_options": null,
+  "optimizer_execution_strategy": "trial_batch_runner",
+  "optimizer_requested_max_workers": "auto",
+  "optimizer_resolved_max_workers": 8,
   "diffraction_order": 1,
   "fourier_orders": 10,
   "angle_mode": "cff",
   "cff": 2.25,
-  "result_json_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_blazed/results/blazed_fit/best_result.json",
-  "trial_history_csv_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_blazed/results/blazed_fit/trial_history.csv",
-  "best_fit_plot_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_blazed/results/blazed_fit/best_fit.png",
-  "loss_history_plot_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_blazed/results/blazed_fit/optimization_loss_history.png"
+  "result_json_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_blazed/results/blazed_fit/best_result.json",
+  "trial_history_csv_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_blazed/results/blazed_fit/trial_history.csv",
+  "best_fit_plot_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_blazed/results/blazed_fit/best_fit.png",
+  "loss_history_plot_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_blazed/results/blazed_fit/optimization_loss_history.png"
 }
\ No newline at end of file
diff --git a/examples/optimizer/optimizer_blazed/results/blazed_fit/optimization_loss_history.png b/examples/optimizer/optimizer_blazed/results/blazed_fit/optimization_loss_history.png
index be314fa..7b8e2e2 100644
Binary files a/examples/optimizer/optimizer_blazed/results/blazed_fit/optimization_loss_history.png and b/examples/optimizer/optimizer_blazed/results/blazed_fit/optimization_loss_history.png differ
diff --git a/examples/optimizer/optimizer_blazed/results/blazed_fit/simulated_curve_fitted.csv b/examples/optimizer/optimizer_blazed/results/blazed_fit/simulated_curve_fitted.csv
index 2736fa2..f9ca277 100644
--- a/examples/optimizer/optimizer_blazed/results/blazed_fit/simulated_curve_fitted.csv
+++ b/examples/optimizer/optimizer_blazed/results/blazed_fit/simulated_curve_fitted.csv
@@ -1,15 +1,15 @@
 case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
-mono-00000000,50.045,4.880034143622709,-10,4.678386970959676e-06,32.03407642483466
-mono-00000000,50.045,4.880034143622709,-9,2.002565806437966e-06,30.390563401396783
-mono-00000000,50.045,4.880034143622709,-8,5.110225692995849e-06,28.66238747828428
-mono-00000000,50.045,4.880034143622709,-7,3.0369807479758893e-05,26.83306829812136
-mono-00000000,50.045,4.880034143622709,-6,1.8521783196551427e-05,24.880171664681967
-mono-00000000,50.045,4.880034143622709,-5,1.8975496733813164e-05,22.771782017983327
-mono-00000000,50.045,4.880034143622709,-4,0.0002509923475839781,20.45972785882188
-mono-00000000,50.045,4.880034143622709,-3,0.0002727193678765724,17.86493378480536
-mono-00000000,50.045,4.880034143622709,-2,0.0005441224806627905,14.83961112712636
-mono-00000000,50.045,4.880034143622709,-1,0.04031029654367879,11.034899121714332
-mono-00000000,50.045,4.880034143622709,0,0.8153838550384832,4.880034143622737
+mono-00000000,50.045,4.880034143622709,-10,2.9607344016415597e-06,32.03407642483466
+mono-00000000,50.045,4.880034143622709,-9,1.44444390951024e-06,30.390563401396783
+mono-00000000,50.045,4.880034143622709,-8,3.0700792216830355e-06,28.66238747828428
+mono-00000000,50.045,4.880034143622709,-7,2.1565717434913626e-05,26.83306829812136
+mono-00000000,50.045,4.880034143622709,-6,1.4636505429073492e-05,24.880171664681967
+mono-00000000,50.045,4.880034143622709,-5,1.2982206322264017e-05,22.771782017983327
+mono-00000000,50.045,4.880034143622709,-4,0.00019687470608324947,20.45972785882188
+mono-00000000,50.045,4.880034143622709,-3,0.00023104031934097642,17.86493378480536
+mono-00000000,50.045,4.880034143622709,-2,0.00044162810157210143,14.83961112712636
+mono-00000000,50.045,4.880034143622709,-1,0.035526326052414736,11.034899121714332
+mono-00000000,50.045,4.880034143622709,0,0.7544658179966702,4.880034143622737
 mono-00000000,50.045,4.880034143622709,1,0.0,0.0
 mono-00000000,50.045,4.880034143622709,2,0.0,0.0
 mono-00000000,50.045,4.880034143622709,3,0.0,0.0
@@ -20,38 +20,17 @@ mono-00000000,50.045,4.880034143622709,7,0.0,0.0
 mono-00000000,50.045,4.880034143622709,8,0.0,0.0
 mono-00000000,50.045,4.880034143622709,9,0.0,0.0
 mono-00000000,50.045,4.880034143622709,10,0.0,0.0
-mono-00000010,57.549,4.55335847744027,-10,5.183919017634401e-06,29.820964651190273
-mono-00000010,57.549,4.55335847744027,-9,3.1514085762191336e-06,28.29610507094654
-mono-00000010,57.549,4.55335847744027,-8,4.0694098790194025e-06,26.691809749441184
-mono-00000010,57.549,4.55335847744027,-7,3.3126625752e-05,24.99269849210836
-mono-00000010,57.549,4.55335847744027,-6,2.6096418658064073e-05,23.1778354864678
-mono-00000010,57.549,4.55335847744027,-5,1.42619118208997e-05,21.217438747204085
-mono-00000010,57.549,4.55335847744027,-4,0.00027297214459027857,19.066561243942104
-mono-00000010,57.549,4.55335847744027,-3,0.0003631054162726358,16.65142976464307
-mono-00000010,57.549,4.55335847744027,-2,0.00045846286160475263,13.834187591702204
-mono-00000010,57.549,4.55335847744027,-1,0.04587482503744788,10.28949452111388
-mono-00000010,57.549,4.55335847744027,0,0.8039961319861653,4.553358477440241
-mono-00000010,57.549,4.55335847744027,1,0.0,0.0
-mono-00000010,57.549,4.55335847744027,2,0.0,0.0
-mono-00000010,57.549,4.55335847744027,3,0.0,0.0
-mono-00000010,57.549,4.55335847744027,4,0.0,0.0
-mono-00000010,57.549,4.55335847744027,5,0.0,0.0
-mono-00000010,57.549,4.55335847744027,6,0.0,0.0
-mono-00000010,57.549,4.55335847744027,7,0.0,0.0
-mono-00000010,57.549,4.55335847744027,8,0.0,0.0
-mono-00000010,57.549,4.55335847744027,9,0.0,0.0
-mono-00000010,57.549,4.55335847744027,10,0.0,0.0
-mono-00000001,50.796,4.84413830130174,-10,4.717131579684789e-06,31.79012523717897
-mono-00000001,50.796,4.84413830130174,-9,2.0980589414621966e-06,30.15974974922453
-mono-00000001,50.796,4.84413830130174,-8,4.978002102637428e-06,28.445279931113525
-mono-00000001,50.796,4.84413830130174,-7,3.0546824739030625e-05,26.630356369479863
-mono-00000001,50.796,4.84413830130174,-6,1.9165361956220828e-05,24.692709564858518
-mono-00000001,50.796,4.84413830130174,-5,1.8426234301719488e-05,22.60065845528048
-mono-00000001,50.796,4.84413830130174,-4,0.00025266979095311075,20.306385939313813
-mono-00000001,50.796,4.84413830130174,-3,0.0002806382709176375,17.73139941623694
-mono-00000001,50.796,4.84413830130174,-2,0.0005347640814969962,14.729002076732911
-mono-00000001,50.796,4.84413830130174,-1,0.040807525506477774,10.952919565040716
-mono-00000001,50.796,4.84413830130174,0,0.8134566455370351,4.84413830130174
+mono-00000001,50.796,4.84413830130174,-10,2.992741034013075e-06,31.79012523717897
+mono-00000001,50.796,4.84413830130174,-9,1.5174361118809673e-06,30.15974974922453
+mono-00000001,50.796,4.84413830130174,-8,2.9883791091918656e-06,28.445279931113525
+mono-00000001,50.796,4.84413830130174,-7,2.1735804856787084e-05,26.630356369479863
+mono-00000001,50.796,4.84413830130174,-6,1.516943518358151e-05,24.692709564858518
+mono-00000001,50.796,4.84413830130174,-5,1.2611046163442725e-05,22.60065845528048
+mono-00000001,50.796,4.84413830130174,-4,0.00019868029876006935,20.306385939313813
+mono-00000001,50.796,4.84413830130174,-3,0.00023825086925000896,17.73139941623694
+mono-00000001,50.796,4.84413830130174,-2,0.00043469680791239154,14.729002076732911
+mono-00000001,50.796,4.84413830130174,-1,0.0360308637941618,10.952919565040716
+mono-00000001,50.796,4.84413830130174,0,0.7535340277796736,4.84413830130174
 mono-00000001,50.796,4.84413830130174,1,0.0,0.0
 mono-00000001,50.796,4.84413830130174,2,0.0,0.0
 mono-00000001,50.796,4.84413830130174,3,0.0,0.0
@@ -62,59 +41,17 @@ mono-00000001,50.796,4.84413830130174,7,0.0,0.0
 mono-00000001,50.796,4.84413830130174,8,0.0,0.0
 mono-00000001,50.796,4.84413830130174,9,0.0,0.0
 mono-00000001,50.796,4.84413830130174,10,0.0,0.0
-mono-00000016,62.045,4.3864868554830565,-10,5.616963238417014e-06,28.696297656376615
-mono-00000016,62.045,4.3864868554830565,-9,4.0699001672805924e-06,27.231297232040802
-mono-00000016,62.045,4.3864868554830565,-8,3.6917995375971712e-06,25.689574049573523
-mono-00000016,62.045,4.3864868554830565,-7,3.6106524406248294e-05,24.056309598219116
-mono-00000016,62.045,4.3864868554830565,-6,3.2375393772438485e-05,22.311333199234923
-mono-00000016,62.045,4.3864868554830565,-5,1.2168692531184118e-05,20.4259524263083
-mono-00000016,62.045,4.3864868554830565,-4,0.0002941620451536682,18.356866826637045
-mono-00000016,62.045,4.3864868554830565,-3,0.0004347722662426481,16.033010346408915
-mono-00000016,62.045,4.3864868554830565,-2,0.0004163698836087464,13.321595882923049
-mono-00000016,62.045,4.3864868554830565,-1,0.050199656091886,9.909283474941716
-mono-00000016,62.045,4.3864868554830565,0,0.8076104965561404,4.38648685548317
-mono-00000016,62.045,4.3864868554830565,1,0.0,0.0
-mono-00000016,62.045,4.3864868554830565,2,0.0,0.0
-mono-00000016,62.045,4.3864868554830565,3,0.0,0.0
-mono-00000016,62.045,4.3864868554830565,4,0.0,0.0
-mono-00000016,62.045,4.3864868554830565,5,0.0,0.0
-mono-00000016,62.045,4.3864868554830565,6,0.0,0.0
-mono-00000016,62.045,4.3864868554830565,7,0.0,0.0
-mono-00000016,62.045,4.3864868554830565,8,0.0,0.0
-mono-00000016,62.045,4.3864868554830565,9,0.0,0.0
-mono-00000016,62.045,4.3864868554830565,10,0.0,0.0
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 mono-00001163,1878.59,0.7998827406493376,3,0.0,0.0
@@ -24464,3 +24443,24 @@ mono-00001163,1878.59,0.7998827406493376,7,0.0,0.0
 mono-00001163,1878.59,0.7998827406493376,8,0.0,0.0
 mono-00001163,1878.59,0.7998827406493376,9,0.0,0.0
 mono-00001163,1878.59,0.7998827406493376,10,0.0,0.0
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diff --git a/examples/optimizer/optimizer_blazed/results/blazed_fit/simulated_curve_initial.csv b/examples/optimizer/optimizer_blazed/results/blazed_fit/simulated_curve_initial.csv
index 5ba0fa1..9d467cf 100644
--- a/examples/optimizer/optimizer_blazed/results/blazed_fit/simulated_curve_initial.csv
+++ b/examples/optimizer/optimizer_blazed/results/blazed_fit/simulated_curve_initial.csv
@@ -1,15 +1,15 @@
 case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
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 mono-00000000,50.045,4.880034143622709,1,0.0,0.0
 mono-00000000,50.045,4.880034143622709,2,0.0,0.0
 mono-00000000,50.045,4.880034143622709,3,0.0,0.0
@@ -20,59 +20,17 @@ mono-00000000,50.045,4.880034143622709,7,0.0,0.0
 mono-00000000,50.045,4.880034143622709,8,0.0,0.0
 mono-00000000,50.045,4.880034143622709,9,0.0,0.0
 mono-00000000,50.045,4.880034143622709,10,0.0,0.0
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+mono-00001163,1878.59,0.7998827406493376,8,0.0,0.0
+mono-00001163,1878.59,0.7998827406493376,9,0.0,0.0
+mono-00001163,1878.59,0.7998827406493376,10,0.0,0.0
+mono-00001164,1882.526,0.7990462951634925,-10,2.5218083269095773e-05,5.157560956495217
+mono-00001164,1882.526,0.7990462951634925,-9,4.3333916695439284e-05,4.899254845949656
+mono-00001164,1882.526,0.7990462951634925,-8,0.00010388948925021453,4.62658662494961
+mono-00001164,1882.526,0.7990462951634925,-7,0.00012950595655951316,4.336848183792355
+mono-00001164,1882.526,0.7990462951634925,-6,0.000302703613370364,4.026356051122079
+mono-00001164,1882.526,0.7990462951634925,-5,0.0010663059756918817,3.689874839774376
+mono-00001164,1882.526,0.7990462951634925,-4,0.0010467854889801304,3.319510793670659
+mono-00001164,1882.526,0.7990462951634925,-3,0.029062650288698092,2.902321427824859
+mono-00001164,1882.526,0.7990462951634925,-2,0.11042198916350711,2.414151923204372
+mono-00001164,1882.526,0.7990462951634925,-1,0.16250984691045905,1.7980910196151143
+mono-00001164,1882.526,0.7990462951634925,0,0.399185085012625,0.7990462951633646
 mono-00001164,1882.526,0.7990462951634925,1,0.0,0.0
 mono-00001164,1882.526,0.7990462951634925,2,0.0,0.0
 mono-00001164,1882.526,0.7990462951634925,3,0.0,0.0
diff --git a/examples/optimizer/optimizer_blazed/results/blazed_fit/trial_history.csv b/examples/optimizer/optimizer_blazed/results/blazed_fit/trial_history.csv
index 39bcdbe..fda89b5 100644
--- a/examples/optimizer/optimizer_blazed/results/blazed_fit/trial_history.csv
+++ b/examples/optimizer/optimizer_blazed/results/blazed_fit/trial_history.csv
@@ -1,51 +1,51 @@
 trial_index,loss,blaze_angle_deg,anti_blaze_angle_deg,top_cap_thickness_nm
-0,0.0011434884138970182,0.6396311894059181,3.367457628250122,1.573906773328781
-1,0.004890455376601125,0.9845458030700683,7.691959336400032,1.1327106728218495
-2,0.00628117907342419,1.0953843771480023,4.370165094733238,1.6395670093595982
-3,0.0003146434631264611,0.7504695985466241,8.695170380175114,0.37329976567998524
-4,0.00031941775963897174,0.7813434237614274,5.02794586867094,0.8940842849202453
-5,0.011001078819576831,1.1254892428405583,9.906539529561996,1.3344568017870189
-6,0.0006944039316815531,0.6961659931875914,8.557537717551545,2.0
-7,0.0002941175561295644,0.6825037724335992,5.90799228629614,0.3
-8,0.0023104624249966725,0.5,10.0,0.3
-9,0.00017672662294881996,0.7364879664241047,6.45890004114299,0.3
-10,0.00026300176448483645,0.7968155267666718,2.0,0.3
-11,0.00010873469689235653,0.822468116733834,2.0,2.0
-12,0.00030935678564995573,0.6823573070223485,10.0,0.3
-13,3.716544283357369e-05,0.8525713741125038,2.0,2.0
-14,0.0002500346381654462,0.7941406160405704,2.0,2.0
-15,0.0019936963063438683,0.8564598325092607,10.0,2.0
-16,7.633367499027369e-05,0.8502829678373108,2.0,1.0898054915485547
-17,4.099934911438569e-05,0.8471054565589172,2.0,2.0
-18,0.0044810705955197015,1.2,2.0,0.3
-19,0.0038418328700461544,1.2,2.0,2.0
-20,0.0038168473532485775,0.5,2.0,0.3
-21,3.567733394696939e-05,0.8555120909774052,2.0,2.0
-22,3.70280975651881e-05,0.8528884596153036,2.0,2.0
-23,3.621607510020925e-05,0.854342236743277,2.0,2.0
-24,3.514762304590491e-05,0.8567514981953759,2.0,2.0
-25,3.528012083322499e-05,0.8538179608012029,2.0,1.8707526638116379
-26,3.567733394696939e-05,0.8555290635772181,2.0,2.0
-27,4.879074004376509e-05,0.8519810689492145,2.0,1.821819862271385
-28,3.5771614672228386e-05,0.8531110254103462,2.0,1.9118125658447334
-29,4.9144374574561204e-05,0.8507146124570317,2.0,1.7796776668410774
-30,0.0002877076602123935,0.7358507158587871,10.0,0.3
-31,3.422211971978115e-05,0.8594103033260448,2.0,2.0
-32,8.677926106287766e-05,0.7430456276097716,4.442976891244935,0.3
-33,0.0005074415551755121,0.7597278948257641,2.0,0.6593518924596296
-34,0.0020545189148644324,0.5186313965064144,10.0,2.0
-35,0.0008637919442594475,0.637815469787637,10.0,1.256502660986796
-36,6.624552305257302e-05,0.8065814923645234,3.165808670810621,0.3
-37,4.434747302935836e-05,0.8429991092853486,2.4027990053438364,2.0
-38,0.000351434128796386,0.7529848122034721,3.990534561502549,2.0
-39,0.0002186515783257061,0.8963119940128229,2.0,0.7458620327758206
-40,0.00044861811182097324,0.9235303231753381,2.0,0.39627781886113445
-41,0.00011893465034695,0.8889613217829899,2.0,1.1334942267205845
-42,0.0002527501909467942,0.8394566552918223,3.236259838600462,0.6991080752192343
-43,0.00023233077152496107,0.7968226290030757,4.207521205089455,0.3
-44,0.0035359835335291444,0.5,2.0,2.0
-45,0.00037219303613423985,0.7067428024593677,6.824618504835598,1.0001285644499147
-46,0.0002465724091091303,0.7186270373212326,5.416565741991953,0.7645511430723863
-47,0.0003695429719400594,0.7175307011037474,7.660710147087295,0.9833897046598163
-48,0.0008305736123817181,0.811921698694704,5.769255106003573,2.0
-49,4.214826786124025e-05,0.7811103029983321,3.2919068464974783,0.4633684271772352
+0,0.0011434884138970135,0.6396311894059181,3.367457628250122,1.573906773328781
+1,0.004890455376601045,0.9845458030700683,7.691959336400032,1.1327106728218495
+2,0.006281179073425535,1.0953843771480023,4.370165094733238,1.6395670093595982
+3,0.00031464346312655894,0.7504695985466241,8.695170380175114,0.37329976567998524
+4,0.0003194177596388951,0.7813434237614274,5.02794586867094,0.8940842849202453
+5,0.011001078819576283,1.1254892428405583,9.906539529561996,1.3344568017870189
+6,0.0006944039316813538,0.6961665137436517,8.557522955167975,2.0
+7,0.00018638446438587846,0.713159920282687,6.634374822503521,0.3
+8,0.00021789258259816995,0.8176301643242454,2.0,0.3
+9,0.0023104624249965264,0.5,10.0,0.3
+10,0.00012315544456043237,0.7568870789981612,4.732460844029194,0.3
+11,0.00043883176642074424,0.7653688022394676,2.0,0.3
+12,0.00022519151674664555,0.7716079669899476,5.369526907453883,0.3
+13,0.00025298731103951146,0.7050746668388898,10.0,0.3
+14,9.041488614401696e-05,0.8302863753236313,2.0,2.0
+15,3.596153849485116e-05,0.8549448319454674,2.0,2.0
+16,3.3463965945170985e-05,0.864275074276404,2.0,2.0
+17,8.210369199940213e-05,0.8555670986874386,2.4500708059122487,2.0
+18,3.701677217682658e-05,0.861586967939022,2.0,1.743888083317901
+19,3.3688916241625505e-05,0.8615408087041719,2.0,2.0
+20,0.0009291957599342829,0.7788470348331519,10.0,2.0
+21,0.00025065945362563773,0.8890778201739314,2.0,0.3
+22,3.377257225424056e-05,0.8610028209895382,2.0,1.944937342599791
+23,3.3608804977307794e-05,0.8628419123162161,2.0,2.0
+24,3.403163191693262e-05,0.8602869616750703,2.0,2.0
+25,8.503696372486222e-05,0.8018783087449413,3.4458983291176346,0.3
+26,0.00035297063277447066,0.6710411324357026,8.469925208927014,0.3
+27,0.0025532438265068536,0.5,4.55883412628623,0.3
+28,3.3685522168989315e-05,0.8622189983880982,2.0,2.0
+29,0.004481070595519202,1.2,2.0,0.3
+30,3.3729366129139676e-05,0.8628116171423152,2.0,1.9410972838882208
+31,3.3584373226244034e-05,0.8622011906181971,2.0,2.0
+32,3.337231955210161e-05,0.8654234101472872,2.0,2.0
+33,3.370862292744406e-05,0.8644536682803384,2.0,1.9515598016730689
+34,3.3809959166228906e-05,0.8612851246733725,2.0,1.9281292525262759
+35,3.331287998447174e-05,0.8641036454094532,2.0,2.0
+36,3.375994579295409e-05,0.8615913219192095,2.0,1.9625551189984143
+37,0.012361804900913015,1.2,6.814880770583983,0.3
+38,3.3538269273035906e-05,0.8682876832401322,2.0,2.0
+39,3.3502942191388005e-05,0.8633457425670988,2.0,2.0
+40,3.352262915917651e-05,0.8653418344467927,2.0,1.966671946378524
+41,0.00039905860242623426,0.6674454869706006,5.582449095702284,0.3
+42,0.0008178829235139454,1.004670590822886,2.0,2.0
+43,3.3587453690877797e-05,0.8633921993145243,2.0,1.965561400340118
+44,3.341057932451176e-05,0.8645700719585214,2.0,2.0
+45,0.0003922807331689165,0.8537123324463984,3.2718426238010836,0.3
+46,4.638052001458306e-05,0.7734317507524144,3.5331842984154624,0.3
+47,8.148414815736857e-05,0.7906083455636284,3.19368591869461,0.9372902084665028
+48,0.0033958311722367077,0.9242194915965927,10.0,0.3
+49,0.0035359835335288504,0.5,2.0,2.0
diff --git a/examples/optimizer/optimizer_blazed/run_all.sh b/examples/optimizer/optimizer_blazed/run_all.sh
index 44a1377..42b83c9 100755
--- a/examples/optimizer/optimizer_blazed/run_all.sh
+++ b/examples/optimizer/optimizer_blazed/run_all.sh
@@ -2,8 +2,16 @@
 set -euo pipefail
 
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+PYTHON_BIN="${PYTHON_BIN:-python}"
 
-# python "${SCRIPT_DIR}/0_fit_blazed_grating.py"
-# python "${SCRIPT_DIR}/1_run_simulation_design_parameters.py"
-python "${SCRIPT_DIR}/2_run_simulation_fitted_parameters.py"
-python "${SCRIPT_DIR}/3_plot_blazed_fit_comparison.py"
+echo "==> Running 0_fit_blazed_grating.py"
+"${PYTHON_BIN}" "${SCRIPT_DIR}/0_fit_blazed_grating.py"
+
+echo "==> Running 1_run_simulation_design_parameters.py"
+"${PYTHON_BIN}" "${SCRIPT_DIR}/1_run_simulation_design_parameters.py"
+
+echo "==> Running 2_run_simulation_fitted_parameters.py"
+"${PYTHON_BIN}" "${SCRIPT_DIR}/2_run_simulation_fitted_parameters.py"
+
+echo "==> Running 3_plot_blazed_fit_comparison.py"
+"${PYTHON_BIN}" "${SCRIPT_DIR}/3_plot_blazed_fit_comparison.py"
diff --git a/examples/optimizer/optimizer_laminar/0_fit_laminar_grating.py b/examples/optimizer/optimizer_laminar/0_fit_laminar_grating.py
index fa581fe..1695a85 100644
--- a/examples/optimizer/optimizer_laminar/0_fit_laminar_grating.py
+++ b/examples/optimizer/optimizer_laminar/0_fit_laminar_grating.py
@@ -107,39 +107,45 @@ def build_grating(parameters: dict[str, float]) -> LaminarGrating:
     "max_workers": optimizer_max_workers,
 }
 
-try:
-    result = optimize_to_measurements(spec)
-except ImportError as error:
-    print(error)
-    print("Install the optional optimizer dependency first: `pip install .[opt]`.")
-    raise SystemExit(1) from error
-
-fitted_parameters_path = results_dir / "fitted_parameters.json"
-payload = json.loads(result.result_json_path.read_text(encoding="utf-8"))
-payload["result_json_path"] = str(result.result_json_path)
-payload["trial_history_csv_path"] = str(result.trial_history_csv_path)
-payload["best_fit_plot_path"] = (
-    None if result.best_fit_plot_path is None else str(result.best_fit_plot_path)
-)
-payload["loss_history_plot_path"] = (
-    None if result.loss_history_plot_path is None else str(result.loss_history_plot_path)
-)
-fitted_parameters_path.write_text(json.dumps(payload, indent=2), encoding="utf-8")
-
-print(f"Measurement: {result.measurement_path}")
-print(f"Optimizer backend request: {optimizer_backend}")
-print(f"Optimizer max_workers request: {optimizer_max_workers}")
-print(f"Batch size: {batch_size}")
-print(f"Best loss: {result.best_loss:.6g}")
-print(f"Best parameters: {result.best_parameters}")
-print(f"Completed trials: {result.completed_trials}")
-print(f"Stopped early: {result.stopped_early}")
-if result.early_stop_reason is not None:
-    print(f"Early-stop reason: {result.early_stop_reason}")
-print(f"Fitted parameters JSON: {fitted_parameters_path}")
-print(f"Best result JSON: {result.result_json_path}")
-print(f"Trial history CSV: {result.trial_history_csv_path}")
-if result.best_fit_plot_path is not None:
-    print(f"Best-fit plot: {result.best_fit_plot_path}")
-if result.loss_history_plot_path is not None:
-    print(f"Loss-history plot: {result.loss_history_plot_path}")
+
+def main() -> None:
+    try:
+        result = optimize_to_measurements(spec)
+    except ImportError as error:
+        print(error)
+        print("Install the optional optimizer dependency first: `pip install .[opt]`.")
+        raise SystemExit(1) from error
+
+    fitted_parameters_path = results_dir / "fitted_parameters.json"
+    payload = json.loads(result.result_json_path.read_text(encoding="utf-8"))
+    payload["result_json_path"] = str(result.result_json_path)
+    payload["trial_history_csv_path"] = str(result.trial_history_csv_path)
+    payload["best_fit_plot_path"] = (
+        None if result.best_fit_plot_path is None else str(result.best_fit_plot_path)
+    )
+    payload["loss_history_plot_path"] = (
+        None if result.loss_history_plot_path is None else str(result.loss_history_plot_path)
+    )
+    fitted_parameters_path.write_text(json.dumps(payload, indent=2), encoding="utf-8")
+
+    print(f"Measurement: {result.measurement_path}")
+    print(f"Optimizer backend request: {optimizer_backend}")
+    print(f"Optimizer max_workers request: {optimizer_max_workers}")
+    print(f"Batch size: {batch_size}")
+    print(f"Best loss: {result.best_loss:.6g}")
+    print(f"Best parameters: {result.best_parameters}")
+    print(f"Completed trials: {result.completed_trials}")
+    print(f"Stopped early: {result.stopped_early}")
+    if result.early_stop_reason is not None:
+        print(f"Early-stop reason: {result.early_stop_reason}")
+    print(f"Fitted parameters JSON: {fitted_parameters_path}")
+    print(f"Best result JSON: {result.result_json_path}")
+    print(f"Trial history CSV: {result.trial_history_csv_path}")
+    if result.best_fit_plot_path is not None:
+        print(f"Best-fit plot: {result.best_fit_plot_path}")
+    if result.loss_history_plot_path is not None:
+        print(f"Loss-history plot: {result.loss_history_plot_path}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/optimizer/optimizer_laminar/0b_fit_laminar_grating_tied_walls.py b/examples/optimizer/optimizer_laminar/0b_fit_laminar_grating_tied_walls.py
index 9aaa3c6..717d988 100644
--- a/examples/optimizer/optimizer_laminar/0b_fit_laminar_grating_tied_walls.py
+++ b/examples/optimizer/optimizer_laminar/0b_fit_laminar_grating_tied_walls.py
@@ -109,39 +109,45 @@ def build_grating(parameters: dict[str, float]) -> LaminarGrating:
     "max_workers": optimizer_max_workers,
 }
 
-try:
-    result = optimize_to_measurements(spec)
-except ImportError as error:
-    print(error)
-    print("Install the optional optimizer dependency first: `pip install .[opt]`.")
-    raise SystemExit(1) from error
-
-fitted_parameters_path = tied_wall_results_dir / "fitted_parameters.json"
-payload = json.loads(result.result_json_path.read_text(encoding="utf-8"))
-payload["result_json_path"] = str(result.result_json_path)
-payload["trial_history_csv_path"] = str(result.trial_history_csv_path)
-payload["best_fit_plot_path"] = (
-    None if result.best_fit_plot_path is None else str(result.best_fit_plot_path)
-)
-payload["loss_history_plot_path"] = (
-    None if result.loss_history_plot_path is None else str(result.loss_history_plot_path)
-)
-fitted_parameters_path.write_text(json.dumps(payload, indent=2), encoding="utf-8")
-
-print(f"Measurement: {result.measurement_path}")
-print(f"Optimizer backend request: {optimizer_backend}")
-print(f"Optimizer max_workers request: {optimizer_max_workers}")
-print(f"Batch size: {batch_size}")
-print(f"Best loss: {result.best_loss:.6g}")
-print(f"Best parameters: {result.best_parameters}")
-print(f"Completed trials: {result.completed_trials}")
-print(f"Stopped early: {result.stopped_early}")
-if result.early_stop_reason is not None:
-    print(f"Early-stop reason: {result.early_stop_reason}")
-print(f"Fitted parameters JSON: {fitted_parameters_path}")
-print(f"Best result JSON: {result.result_json_path}")
-print(f"Trial history CSV: {result.trial_history_csv_path}")
-if result.best_fit_plot_path is not None:
-    print(f"Best-fit plot: {result.best_fit_plot_path}")
-if result.loss_history_plot_path is not None:
-    print(f"Loss-history plot: {result.loss_history_plot_path}")
+
+def main() -> None:
+    try:
+        result = optimize_to_measurements(spec)
+    except ImportError as error:
+        print(error)
+        print("Install the optional optimizer dependency first: `pip install .[opt]`.")
+        raise SystemExit(1) from error
+
+    fitted_parameters_path = tied_wall_results_dir / "fitted_parameters.json"
+    payload = json.loads(result.result_json_path.read_text(encoding="utf-8"))
+    payload["result_json_path"] = str(result.result_json_path)
+    payload["trial_history_csv_path"] = str(result.trial_history_csv_path)
+    payload["best_fit_plot_path"] = (
+        None if result.best_fit_plot_path is None else str(result.best_fit_plot_path)
+    )
+    payload["loss_history_plot_path"] = (
+        None if result.loss_history_plot_path is None else str(result.loss_history_plot_path)
+    )
+    fitted_parameters_path.write_text(json.dumps(payload, indent=2), encoding="utf-8")
+
+    print(f"Measurement: {result.measurement_path}")
+    print(f"Optimizer backend request: {optimizer_backend}")
+    print(f"Optimizer max_workers request: {optimizer_max_workers}")
+    print(f"Batch size: {batch_size}")
+    print(f"Best loss: {result.best_loss:.6g}")
+    print(f"Best parameters: {result.best_parameters}")
+    print(f"Completed trials: {result.completed_trials}")
+    print(f"Stopped early: {result.stopped_early}")
+    if result.early_stop_reason is not None:
+        print(f"Early-stop reason: {result.early_stop_reason}")
+    print(f"Fitted parameters JSON: {fitted_parameters_path}")
+    print(f"Best result JSON: {result.result_json_path}")
+    print(f"Trial history CSV: {result.trial_history_csv_path}")
+    if result.best_fit_plot_path is not None:
+        print(f"Best-fit plot: {result.best_fit_plot_path}")
+    if result.loss_history_plot_path is not None:
+        print(f"Loss-history plot: {result.loss_history_plot_path}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/optimizer/optimizer_laminar/1_run_simulation_design_parameters.py b/examples/optimizer/optimizer_laminar/1_run_simulation_design_parameters.py
index 257f606..512cb28 100644
--- a/examples/optimizer/optimizer_laminar/1_run_simulation_design_parameters.py
+++ b/examples/optimizer/optimizer_laminar/1_run_simulation_design_parameters.py
@@ -27,80 +27,87 @@
     z_resolution_nm,
 )
 
-results_dir.mkdir(parents=True, exist_ok=True)
 
-silicon = pd.read_csv(
-    optical_constants_dir / "n_Si_cxro.txt",
-    skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-silicon.attrs["name"] = "Si"
+def main() -> None:
 
-platinum = pd.read_csv(
-    optical_constants_dir / "n_Pt_cxro.txt",
-    skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-platinum.attrs["name"] = "Pt"
+    results_dir.mkdir(parents=True, exist_ok=True)
 
-carbon = pd.read_csv(
-    optical_constants_dir / "n_C_cxro.txt",
-    skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-carbon.attrs["name"] = "C"
+    silicon = pd.read_csv(
+        optical_constants_dir / "n_Si_cxro.txt",
+        skiprows=1,
+        sep=r"\s*,\s*|\s+",
+        engine="python",
+    )
+    silicon.attrs["name"] = "Si"
 
-measurement = pd.read_csv(
-    measurement_path,
-    sep=";",
-    skiprows=3,
-    decimal=",",
-    names=["energy_ev", "efficiency"],
-).dropna()
-energies = np.asarray(measurement["energy_ev"], dtype=float)
-
-design_grating = grax.LaminarGrating(
-    period_lpermm=period_lpermm,
-    width_to_period_ratio=width_to_period_ratio,
-    depth_nm=depth_nm,
-    left_wall_angle_deg=left_wall_angle_deg,
-    right_wall_angle_deg=right_wall_angle_deg,
-    substrate_material=silicon,
-    layer_material=platinum,
-    layer_thickness_nm=layer_thickness_nm,
-    top_cap_material=carbon,
-    top_cap_thickness_nm=top_cap_thickness_nm,
-    z_resolution_nm=z_resolution_nm,
-    x_resolution_nm=x_resolution_nm,
-)
+    platinum = pd.read_csv(
+        optical_constants_dir / "n_Pt_cxro.txt",
+        skiprows=1,
+        sep=r"\s*,\s*|\s+",
+        engine="python",
+    )
+    platinum.attrs["name"] = "Pt"
 
-cases = grax.fixed_angle_cases(
-    grating=design_grating,
-    energies_ev=energies,
-    grazing_angle_deg=grazing_angle_deg,
-    polarization="p",
-)
+    carbon = pd.read_csv(
+        optical_constants_dir / "n_C_cxro.txt",
+        skiprows=1,
+        sep=r"\s*,\s*|\s+",
+        engine="python",
+    )
+    carbon.attrs["name"] = "C"
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=diffraction_order,
-    default_fourier_orders=fourier_orders,
-    max_workers="auto",
-    show_progress=True,
-    live_plot=False,
-    on_error="fail_fast",
-    backend="numba",
-)
-results = list(runner.run_cases(cases))
+    measurement = pd.read_csv(
+        measurement_path,
+        sep=";",
+        skiprows=3,
+        decimal=",",
+        names=["energy_ev", "efficiency"],
+    ).dropna()
+    energies = np.asarray(measurement["energy_ev"], dtype=float)
 
-output_csv_path = results_dir / "simulated_curve_initial.csv"
-grax.write_all_orders_csv(results, output_csv_path)
+    design_grating = grax.LaminarGrating(
+        period_lpermm=period_lpermm,
+        width_to_period_ratio=width_to_period_ratio,
+        depth_nm=depth_nm,
+        left_wall_angle_deg=left_wall_angle_deg,
+        right_wall_angle_deg=right_wall_angle_deg,
+        substrate_material=silicon,
+        layer_material=platinum,
+        layer_thickness_nm=layer_thickness_nm,
+        top_cap_material=carbon,
+        top_cap_thickness_nm=top_cap_thickness_nm,
+        z_resolution_nm=z_resolution_nm,
+        x_resolution_nm=x_resolution_nm,
+    )
 
-print(f"Initial-parameter simulation CSV: {output_csv_path}")
-print(
-    "Initial simulation settings: "
-    f"grazing_angle_deg={grazing_angle_deg}, "
-    f"fourier_orders={fourier_orders}, simulation_backend=numba"
-)
+    cases = grax.fixed_angle_cases(
+        grating=design_grating,
+        energies_ev=energies,
+        grazing_angle_deg=grazing_angle_deg,
+        polarization="p",
+    )
+
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=diffraction_order,
+        fourier_orders=fourier_orders,
+        max_workers="auto",
+        show_progress=True,
+        live_plot=True,
+        on_error="fail_fast",
+        backend="numba",
+    )
+    results = list(runner.run_cases(cases))
+
+    output_csv_path = results_dir / "simulated_curve_initial.csv"
+    grax.write_all_orders_csv(results, output_csv_path)
+
+    print(f"Initial-parameter simulation CSV: {output_csv_path}")
+    print(
+        "Initial simulation settings: "
+        f"grazing_angle_deg={grazing_angle_deg}, "
+        f"fourier_orders={fourier_orders}, simulation_backend=numba"
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/optimizer/optimizer_laminar/2_run_simulation_fitted_parameters.py b/examples/optimizer/optimizer_laminar/2_run_simulation_fitted_parameters.py
index cf165f3..c5df521 100644
--- a/examples/optimizer/optimizer_laminar/2_run_simulation_fitted_parameters.py
+++ b/examples/optimizer/optimizer_laminar/2_run_simulation_fitted_parameters.py
@@ -18,79 +18,86 @@
     simulation_backend as baseline_simulation_backend,
 )
 
-results_dir.mkdir(parents=True, exist_ok=True)
 
-fitted_parameters_path = results_dir / "fitted_parameters.json"
-if not fitted_parameters_path.exists():
-    raise FileNotFoundError(
-        f"Missing fitted parameters file: {fitted_parameters_path}. Run 0_fit_laminar_grating.py first."
+def main() -> None:
+
+    results_dir.mkdir(parents=True, exist_ok=True)
+
+    fitted_parameters_path = results_dir / "fitted_parameters.json"
+    if not fitted_parameters_path.exists():
+        raise FileNotFoundError(
+            f"Missing fitted parameters file: {fitted_parameters_path}. Run 0_fit_laminar_grating.py first."
+        )
+
+    silicon = pd.read_csv(
+        optical_constants_dir / "n_Si_cxro.txt",
+        skiprows=1,
+        sep=r"\s*,\s*|\s+",
+        engine="python",
     )
+    silicon.attrs["name"] = "Si"
 
-silicon = pd.read_csv(
-    optical_constants_dir / "n_Si_cxro.txt",
-    skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-silicon.attrs["name"] = "Si"
+    platinum = pd.read_csv(
+        optical_constants_dir / "n_Pt_cxro.txt",
+        skiprows=1,
+        sep=r"\s*,\s*|\s+",
+        engine="python",
+    )
+    platinum.attrs["name"] = "Pt"
 
-platinum = pd.read_csv(
-    optical_constants_dir / "n_Pt_cxro.txt",
-    skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-platinum.attrs["name"] = "Pt"
+    carbon = pd.read_csv(
+        optical_constants_dir / "n_C_cxro.txt",
+        skiprows=1,
+        sep=r"\s*,\s*|\s+",
+        engine="python",
+    )
+    carbon.attrs["name"] = "C"
 
-carbon = pd.read_csv(
-    optical_constants_dir / "n_C_cxro.txt",
-    skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-carbon.attrs["name"] = "C"
+    measurement = pd.read_csv(
+        measurement_path,
+        sep=";",
+        skiprows=3,
+        decimal=",",
+        names=["energy_ev", "efficiency"],
+    ).dropna()
+    energies = np.asarray(measurement["energy_ev"], dtype=float)
 
-measurement = pd.read_csv(
-    measurement_path,
-    sep=";",
-    skiprows=3,
-    decimal=",",
-    names=["energy_ev", "efficiency"],
-).dropna()
-energies = np.asarray(measurement["energy_ev"], dtype=float)
-
-payload = json.loads(fitted_parameters_path.read_text(encoding="utf-8"))
-fitted_grating_parameters = dict(payload["best_grating_parameters"])
-fitted_grating_parameters["substrate_material"] = silicon
-fitted_grating_parameters["layer_material"] = platinum
-fitted_grating_parameters["top_cap_material"] = carbon
-fitted_grating = grax.LaminarGrating(**fitted_grating_parameters)
-
-cases = grax.fixed_angle_cases(
-    grating=fitted_grating,
-    energies_ev=energies,
-    grazing_angle_deg=grazing_angle_deg,
-    polarization="p",
-)
+    payload = json.loads(fitted_parameters_path.read_text(encoding="utf-8"))
+    fitted_grating_parameters = dict(payload["best_grating_parameters"])
+    fitted_grating_parameters["substrate_material"] = silicon
+    fitted_grating_parameters["layer_material"] = platinum
+    fitted_grating_parameters["top_cap_material"] = carbon
+    fitted_grating = grax.LaminarGrating(**fitted_grating_parameters)
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=int(payload.get("diffraction_order", baseline_diffraction_order)),
-    default_fourier_orders=int(payload.get("fourier_orders", baseline_fourier_orders)),
-    max_workers="auto",
-    show_progress=True,
-    live_plot=False,
-    on_error="fail_fast",
-    backend="numba",
-)
-results = list(runner.run_cases(cases))
+    cases = grax.fixed_angle_cases(
+        grating=fitted_grating,
+        energies_ev=energies,
+        grazing_angle_deg=grazing_angle_deg,
+        polarization="p",
+    )
 
-output_csv_path = results_dir / "simulated_curve_fitted.csv"
-grax.write_all_orders_csv(results, output_csv_path)
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=int(payload.get("diffraction_order", baseline_diffraction_order)),
+        fourier_orders=int(payload.get("fourier_orders", baseline_fourier_orders)),
+        max_workers="auto",
+        show_progress=True,
+        live_plot=True,
+        on_error="fail_fast",
+        backend="numba",
+    )
+    results = list(runner.run_cases(cases))
 
-print(f"Fitted-parameter simulation CSV: {output_csv_path}")
-print(
-    "Fitted simulation settings: "
-    f"grazing_angle_deg={grazing_angle_deg}, "
-    f"fourier_orders={int(payload.get('fourier_orders', baseline_fourier_orders))}, "
-    "simulation_backend=numba"
-)
+    output_csv_path = results_dir / "simulated_curve_fitted.csv"
+    grax.write_all_orders_csv(results, output_csv_path)
+
+    print(f"Fitted-parameter simulation CSV: {output_csv_path}")
+    print(
+        "Fitted simulation settings: "
+        f"grazing_angle_deg={grazing_angle_deg}, "
+        f"fourier_orders={int(payload.get('fourier_orders', baseline_fourier_orders))}, "
+        "simulation_backend=numba"
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/optimizer/optimizer_laminar/2b_run_simulation_tied_wall_fitted_parameters.py b/examples/optimizer/optimizer_laminar/2b_run_simulation_tied_wall_fitted_parameters.py
index 353b301..f2f176b 100644
--- a/examples/optimizer/optimizer_laminar/2b_run_simulation_tied_wall_fitted_parameters.py
+++ b/examples/optimizer/optimizer_laminar/2b_run_simulation_tied_wall_fitted_parameters.py
@@ -18,80 +18,87 @@
     simulation_backend as baseline_simulation_backend,
 )
 
-tied_wall_results_dir.mkdir(parents=True, exist_ok=True)
 
-fitted_parameters_path = tied_wall_results_dir / "fitted_parameters.json"
-if not fitted_parameters_path.exists():
-    raise FileNotFoundError(
-        f"Missing fitted parameters file: {fitted_parameters_path}. "
-        "Run 0b_fit_laminar_grating_tied_walls.py first."
+def main() -> None:
+
+    tied_wall_results_dir.mkdir(parents=True, exist_ok=True)
+
+    fitted_parameters_path = tied_wall_results_dir / "fitted_parameters.json"
+    if not fitted_parameters_path.exists():
+        raise FileNotFoundError(
+            f"Missing fitted parameters file: {fitted_parameters_path}. "
+            "Run 0b_fit_laminar_grating_tied_walls.py first."
+        )
+
+    silicon = pd.read_csv(
+        optical_constants_dir / "n_Si_cxro.txt",
+        skiprows=1,
+        sep=r"\s*,\s*|\s+",
+        engine="python",
     )
+    silicon.attrs["name"] = "Si"
 
-silicon = pd.read_csv(
-    optical_constants_dir / "n_Si_cxro.txt",
-    skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-silicon.attrs["name"] = "Si"
+    platinum = pd.read_csv(
+        optical_constants_dir / "n_Pt_cxro.txt",
+        skiprows=1,
+        sep=r"\s*,\s*|\s+",
+        engine="python",
+    )
+    platinum.attrs["name"] = "Pt"
 
-platinum = pd.read_csv(
-    optical_constants_dir / "n_Pt_cxro.txt",
-    skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-platinum.attrs["name"] = "Pt"
+    carbon = pd.read_csv(
+        optical_constants_dir / "n_C_cxro.txt",
+        skiprows=1,
+        sep=r"\s*,\s*|\s+",
+        engine="python",
+    )
+    carbon.attrs["name"] = "C"
 
-carbon = pd.read_csv(
-    optical_constants_dir / "n_C_cxro.txt",
-    skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-carbon.attrs["name"] = "C"
+    measurement = pd.read_csv(
+        measurement_path,
+        sep=";",
+        skiprows=3,
+        decimal=",",
+        names=["energy_ev", "efficiency"],
+    ).dropna()
+    energies = np.asarray(measurement["energy_ev"], dtype=float)
 
-measurement = pd.read_csv(
-    measurement_path,
-    sep=";",
-    skiprows=3,
-    decimal=",",
-    names=["energy_ev", "efficiency"],
-).dropna()
-energies = np.asarray(measurement["energy_ev"], dtype=float)
-
-payload = json.loads(fitted_parameters_path.read_text(encoding="utf-8"))
-fitted_grating_parameters = dict(payload["best_grating_parameters"])
-fitted_grating_parameters["substrate_material"] = silicon
-fitted_grating_parameters["layer_material"] = platinum
-fitted_grating_parameters["top_cap_material"] = carbon
-fitted_grating = grax.LaminarGrating(**fitted_grating_parameters)
-
-cases = grax.fixed_angle_cases(
-    grating=fitted_grating,
-    energies_ev=energies,
-    grazing_angle_deg=grazing_angle_deg,
-    polarization="p",
-)
+    payload = json.loads(fitted_parameters_path.read_text(encoding="utf-8"))
+    fitted_grating_parameters = dict(payload["best_grating_parameters"])
+    fitted_grating_parameters["substrate_material"] = silicon
+    fitted_grating_parameters["layer_material"] = platinum
+    fitted_grating_parameters["top_cap_material"] = carbon
+    fitted_grating = grax.LaminarGrating(**fitted_grating_parameters)
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=int(payload.get("diffraction_order", baseline_diffraction_order)),
-    default_fourier_orders=int(payload.get("fourier_orders", baseline_fourier_orders)),
-    max_workers="auto",
-    show_progress=True,
-    live_plot=False,
-    on_error="fail_fast",
-    backend="numba",
-)
-results = list(runner.run_cases(cases))
+    cases = grax.fixed_angle_cases(
+        grating=fitted_grating,
+        energies_ev=energies,
+        grazing_angle_deg=grazing_angle_deg,
+        polarization="p",
+    )
 
-output_csv_path = tied_wall_results_dir / "simulated_curve_fitted.csv"
-grax.write_all_orders_csv(results, output_csv_path)
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=int(payload.get("diffraction_order", baseline_diffraction_order)),
+        fourier_orders=int(payload.get("fourier_orders", baseline_fourier_orders)),
+        max_workers="auto",
+        show_progress=True,
+        live_plot=True,
+        on_error="fail_fast",
+        backend="numba",
+    )
+    results = list(runner.run_cases(cases))
 
-print(f"Tied-wall fitted-parameter simulation CSV: {output_csv_path}")
-print(
-    "Tied-wall simulation settings: "
-    f"grazing_angle_deg={grazing_angle_deg}, "
-    f"fourier_orders={int(payload.get('fourier_orders', baseline_fourier_orders))}, "
-    "simulation_backend=numba"
-)
+    output_csv_path = tied_wall_results_dir / "simulated_curve_fitted.csv"
+    grax.write_all_orders_csv(results, output_csv_path)
+
+    print(f"Tied-wall fitted-parameter simulation CSV: {output_csv_path}")
+    print(
+        "Tied-wall simulation settings: "
+        f"grazing_angle_deg={grazing_angle_deg}, "
+        f"fourier_orders={int(payload.get('fourier_orders', baseline_fourier_orders))}, "
+        "simulation_backend=numba"
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/optimizer/optimizer_laminar/3_plot_laminar_fit_comparison.py b/examples/optimizer/optimizer_laminar/3_plot_laminar_fit_comparison.py
index 2e00e03..dd4d421 100644
--- a/examples/optimizer/optimizer_laminar/3_plot_laminar_fit_comparison.py
+++ b/examples/optimizer/optimizer_laminar/3_plot_laminar_fit_comparison.py
@@ -8,114 +8,121 @@
 import pandas as pd
 from example_config import measurement_path, results_dir, tied_wall_results_dir
 
-results_dir.mkdir(parents=True, exist_ok=True)
-tied_wall_results_dir.mkdir(parents=True, exist_ok=True)
 
-fitted_parameters_path = results_dir / "fitted_parameters.json"
-tied_wall_fitted_parameters_path = tied_wall_results_dir / "fitted_parameters.json"
-initial_csv_path = results_dir / "simulated_curve_initial.csv"
-fitted_csv_path = results_dir / "simulated_curve_fitted.csv"
-tied_wall_fitted_csv_path = tied_wall_results_dir / "simulated_curve_fitted.csv"
-comparison_plot_path = results_dir / "laminar_fit_measurement_comparison.png"
+def main() -> None:
 
-if not fitted_parameters_path.exists():
-    raise FileNotFoundError(
-        f"Missing fitted parameters file: {fitted_parameters_path}. "
-        "Run 0_fit_laminar_grating.py first."
-    )
-if not tied_wall_fitted_parameters_path.exists():
-    raise FileNotFoundError(
-        f"Missing tied-wall fitted parameters file: {tied_wall_fitted_parameters_path}. "
-        "Run 0b_fit_laminar_grating_tied_walls.py first."
+    results_dir.mkdir(parents=True, exist_ok=True)
+    tied_wall_results_dir.mkdir(parents=True, exist_ok=True)
+
+    fitted_parameters_path = results_dir / "fitted_parameters.json"
+    tied_wall_fitted_parameters_path = tied_wall_results_dir / "fitted_parameters.json"
+    initial_csv_path = results_dir / "simulated_curve_initial.csv"
+    fitted_csv_path = results_dir / "simulated_curve_fitted.csv"
+    tied_wall_fitted_csv_path = tied_wall_results_dir / "simulated_curve_fitted.csv"
+    comparison_plot_path = results_dir / "laminar_fit_measurement_comparison.png"
+
+    if not fitted_parameters_path.exists():
+        raise FileNotFoundError(
+            f"Missing fitted parameters file: {fitted_parameters_path}. "
+            "Run 0_fit_laminar_grating.py first."
+        )
+    if not tied_wall_fitted_parameters_path.exists():
+        raise FileNotFoundError(
+            f"Missing tied-wall fitted parameters file: {tied_wall_fitted_parameters_path}. "
+            "Run 0b_fit_laminar_grating_tied_walls.py first."
+        )
+    if not initial_csv_path.exists():
+        raise FileNotFoundError(
+            f"Missing initial simulation CSV: {initial_csv_path}. "
+            "Run 1_run_simulation_design_parameters.py first."
+        )
+    if not fitted_csv_path.exists():
+        raise FileNotFoundError(
+            f"Missing fitted simulation CSV: {fitted_csv_path}. "
+            "Run 2_run_simulation_fitted_parameters.py first."
+        )
+    if not tied_wall_fitted_csv_path.exists():
+        raise FileNotFoundError(
+            f"Missing tied-wall fitted simulation CSV: {tied_wall_fitted_csv_path}. "
+            "Run 2b_run_simulation_tied_wall_fitted_parameters.py first."
+        )
+
+    measurement = pd.read_csv(
+        measurement_path,
+        sep=";",
+        skiprows=3,
+        decimal=",",
+        names=["energy_ev", "efficiency"],
+    ).dropna()
+    initial_frame = pd.read_csv(initial_csv_path)
+    fitted_frame = pd.read_csv(fitted_csv_path)
+    tied_wall_fitted_frame = pd.read_csv(tied_wall_fitted_csv_path)
+    fitted_parameters = json.loads(fitted_parameters_path.read_text(encoding="utf-8"))
+    tied_wall_fitted_parameters = json.loads(
+        tied_wall_fitted_parameters_path.read_text(encoding="utf-8")
     )
-if not initial_csv_path.exists():
-    raise FileNotFoundError(
-        f"Missing initial simulation CSV: {initial_csv_path}. "
-        "Run 1_run_simulation_design_parameters.py first."
+    evaluation_energies_ev = [
+        float(energy_ev) for energy_ev in fitted_parameters.get("evaluation_energies_ev", [])
+    ]
+    tied_wall_evaluation_energies_ev = [
+        float(energy_ev)
+        for energy_ev in tied_wall_fitted_parameters.get("evaluation_energies_ev", [])
+    ]
+
+    initial_m1 = initial_frame[initial_frame["order"] == -1].sort_values("energy_ev")
+    fitted_m1 = fitted_frame[fitted_frame["order"] == -1].sort_values("energy_ev")
+    tied_wall_fitted_m1 = (
+        tied_wall_fitted_frame[tied_wall_fitted_frame["order"] == -1]
+        .sort_values("energy_ev")
     )
-if not fitted_csv_path.exists():
-    raise FileNotFoundError(
-        f"Missing fitted simulation CSV: {fitted_csv_path}. "
-        "Run 2_run_simulation_fitted_parameters.py first."
+
+    figure, axis = plt.subplots(figsize=(11, 7))
+    axis.plot(
+        measurement["energy_ev"],
+        measurement["efficiency"],
+        "o",
+        label="Measurement",
+        markersize=3.0,
     )
-if not tied_wall_fitted_csv_path.exists():
-    raise FileNotFoundError(
-        f"Missing tied-wall fitted simulation CSV: {tied_wall_fitted_csv_path}. "
-        "Run 2b_run_simulation_tied_wall_fitted_parameters.py first."
+    axis.plot(initial_m1["energy_ev"], initial_m1["efficiency"], "-", label="Initial design")
+    axis.plot(fitted_m1["energy_ev"], fitted_m1["efficiency"], "-", label="Standard fit")
+    axis.plot(
+        tied_wall_fitted_m1["energy_ev"],
+        tied_wall_fitted_m1["efficiency"],
+        "-",
+        label="Tied-wall fit",
     )
+    if evaluation_energies_ev:
+        y_min, y_max = axis.get_ylim()
+        axis.vlines(
+            evaluation_energies_ev,
+            y_min,
+            y_max,
+            colors="red",
+            linestyles=":",
+            linewidth=0.8,
+            label="Optimization energies",
+        )
+        axis.set_ylim(y_min, y_max)
+    if tied_wall_evaluation_energies_ev and tied_wall_evaluation_energies_ev != evaluation_energies_ev:
+        axis.vlines(
+            tied_wall_evaluation_energies_ev,
+            *axis.get_ylim(),
+            colors="purple",
+            linestyles="--",
+            linewidth=0.6,
+            label="Tied-wall energies",
+        )
+    axis.set_xlabel("Energy (eV)")
+    axis.set_ylabel("Efficiency")
+    axis.set_title("Laminar fit: measurement vs initial, standard fit, and tied-wall fit")
+    axis.legend(loc="best")
+    figure.tight_layout()
+    figure.savefig(comparison_plot_path, dpi=200, bbox_inches="tight")
+    plt.close(figure)
 
-measurement = pd.read_csv(
-    measurement_path,
-    sep=";",
-    skiprows=3,
-    decimal=",",
-    names=["energy_ev", "efficiency"],
-).dropna()
-initial_frame = pd.read_csv(initial_csv_path)
-fitted_frame = pd.read_csv(fitted_csv_path)
-tied_wall_fitted_frame = pd.read_csv(tied_wall_fitted_csv_path)
-fitted_parameters = json.loads(fitted_parameters_path.read_text(encoding="utf-8"))
-tied_wall_fitted_parameters = json.loads(
-    tied_wall_fitted_parameters_path.read_text(encoding="utf-8")
-)
-evaluation_energies_ev = [
-    float(energy_ev) for energy_ev in fitted_parameters.get("evaluation_energies_ev", [])
-]
-tied_wall_evaluation_energies_ev = [
-    float(energy_ev)
-    for energy_ev in tied_wall_fitted_parameters.get("evaluation_energies_ev", [])
-]
-
-initial_m1 = initial_frame[initial_frame["order"] == -1].sort_values("energy_ev")
-fitted_m1 = fitted_frame[fitted_frame["order"] == -1].sort_values("energy_ev")
-tied_wall_fitted_m1 = (
-    tied_wall_fitted_frame[tied_wall_fitted_frame["order"] == -1]
-    .sort_values("energy_ev")
-)
+    print(f"Comparison plot: {comparison_plot_path}")
 
-figure, axis = plt.subplots(figsize=(11, 7))
-axis.plot(
-    measurement["energy_ev"],
-    measurement["efficiency"],
-    "o",
-    label="Measurement",
-    markersize=3.0,
-)
-axis.plot(initial_m1["energy_ev"], initial_m1["efficiency"], "-", label="Initial design")
-axis.plot(fitted_m1["energy_ev"], fitted_m1["efficiency"], "-", label="Standard fit")
-axis.plot(
-    tied_wall_fitted_m1["energy_ev"],
-    tied_wall_fitted_m1["efficiency"],
-    "-",
-    label="Tied-wall fit",
-)
-if evaluation_energies_ev:
-    y_min, y_max = axis.get_ylim()
-    axis.vlines(
-        evaluation_energies_ev,
-        y_min,
-        y_max,
-        colors="red",
-        linestyles=":",
-        linewidth=0.8,
-        label="Optimization energies",
-    )
-    axis.set_ylim(y_min, y_max)
-if tied_wall_evaluation_energies_ev and tied_wall_evaluation_energies_ev != evaluation_energies_ev:
-    axis.vlines(
-        tied_wall_evaluation_energies_ev,
-        *axis.get_ylim(),
-        colors="purple",
-        linestyles="--",
-        linewidth=0.6,
-        label="Tied-wall energies",
-    )
-axis.set_xlabel("Energy (eV)")
-axis.set_ylabel("Efficiency")
-axis.set_title("Laminar fit: measurement vs initial, standard fit, and tied-wall fit")
-axis.legend(loc="best")
-figure.tight_layout()
-figure.savefig(comparison_plot_path, dpi=200, bbox_inches="tight")
-plt.close(figure)
 
-print(f"Comparison plot: {comparison_plot_path}")
+if __name__ == "__main__":
+    main()
diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit/best_fit.png b/examples/optimizer/optimizer_laminar/results/laminar_fit/best_fit.png
index f8c668e..0a83962 100644
Binary files a/examples/optimizer/optimizer_laminar/results/laminar_fit/best_fit.png and b/examples/optimizer/optimizer_laminar/results/laminar_fit/best_fit.png differ
diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit/best_result.json b/examples/optimizer/optimizer_laminar/results/laminar_fit/best_result.json
index 843ca75..8e91768 100644
--- a/examples/optimizer/optimizer_laminar/results/laminar_fit/best_result.json
+++ b/examples/optimizer/optimizer_laminar/results/laminar_fit/best_result.json
@@ -2,7 +2,7 @@
   "optimization_mode": "measurement_fit",
   "experiment_name": "laminar_fit",
   "objective_name": "loss",
-  "measurement_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_laminar/measured_alpha4deg_order1.csv",
+  "measurement_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_laminar/measured_alpha4deg_order1.csv",
   "evaluation_mode": "energy_only",
   "evaluation_case_mode": "energy_only",
   "evaluation_energies_ev": [
@@ -72,20 +72,20 @@
     ]
   },
   "equality_constraints": {},
-  "best_loss": 5.266607734459274e-05,
+  "best_loss": 3.073717011236386e-06,
   "best_parameters": {
-    "width_to_period_ratio": 0.705950661777188,
-    "depth_nm": 14.150756203706413,
-    "left_wall_angle_deg": 13.222220727353854,
+    "width_to_period_ratio": 0.7251252862466292,
+    "depth_nm": 14.725038447795153,
+    "left_wall_angle_deg": 10.99163847647662,
     "right_wall_angle_deg": 20.0,
-    "top_cap_thickness_nm": 0.3
+    "top_cap_thickness_nm": 0.8572725775652538
   },
   "best_grating_parameters": {
-    "width_to_period_ratio": 0.705950661777188,
-    "depth_nm": 14.150756203706413,
-    "left_wall_angle_deg": 13.222220727353854,
+    "width_to_period_ratio": 0.7251252862466292,
+    "depth_nm": 14.725038447795153,
+    "left_wall_angle_deg": 10.99163847647662,
     "right_wall_angle_deg": 20.0,
-    "top_cap_thickness_nm": 0.3
+    "top_cap_thickness_nm": 0.8572725775652538
   },
   "best_solver_parameters": {
     "roughness_sigma_nm": null
@@ -95,6 +95,11 @@
   "early_stop_reason": null,
   "backend_requested": "auto",
   "backend_effective": "numba",
+  "solver": "rcwa",
+  "solver_options": null,
+  "optimizer_execution_strategy": "trial_batch_runner",
+  "optimizer_requested_max_workers": "auto",
+  "optimizer_resolved_max_workers": 8,
   "diffraction_order": 1,
   "fourier_orders": 15,
   "angle_mode": "fixed",
diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit/fitted_parameters.json b/examples/optimizer/optimizer_laminar/results/laminar_fit/fitted_parameters.json
index 9ce8fff..1739d15 100644
--- a/examples/optimizer/optimizer_laminar/results/laminar_fit/fitted_parameters.json
+++ b/examples/optimizer/optimizer_laminar/results/laminar_fit/fitted_parameters.json
@@ -2,7 +2,7 @@
   "optimization_mode": "measurement_fit",
   "experiment_name": "laminar_fit",
   "objective_name": "loss",
-  "measurement_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_laminar/measured_alpha4deg_order1.csv",
+  "measurement_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_laminar/measured_alpha4deg_order1.csv",
   "evaluation_mode": "energy_only",
   "evaluation_case_mode": "energy_only",
   "evaluation_energies_ev": [
@@ -72,20 +72,20 @@
     ]
   },
   "equality_constraints": {},
-  "best_loss": 5.266607734459274e-05,
+  "best_loss": 3.073717011236386e-06,
   "best_parameters": {
-    "width_to_period_ratio": 0.705950661777188,
-    "depth_nm": 14.150756203706413,
-    "left_wall_angle_deg": 13.222220727353854,
+    "width_to_period_ratio": 0.7251252862466292,
+    "depth_nm": 14.725038447795153,
+    "left_wall_angle_deg": 10.99163847647662,
     "right_wall_angle_deg": 20.0,
-    "top_cap_thickness_nm": 0.3
+    "top_cap_thickness_nm": 0.8572725775652538
   },
   "best_grating_parameters": {
-    "width_to_period_ratio": 0.705950661777188,
-    "depth_nm": 14.150756203706413,
-    "left_wall_angle_deg": 13.222220727353854,
+    "width_to_period_ratio": 0.7251252862466292,
+    "depth_nm": 14.725038447795153,
+    "left_wall_angle_deg": 10.99163847647662,
     "right_wall_angle_deg": 20.0,
-    "top_cap_thickness_nm": 0.3
+    "top_cap_thickness_nm": 0.8572725775652538
   },
   "best_solver_parameters": {
     "roughness_sigma_nm": null
@@ -95,12 +95,17 @@
   "early_stop_reason": null,
   "backend_requested": "auto",
   "backend_effective": "numba",
+  "solver": "rcwa",
+  "solver_options": null,
+  "optimizer_execution_strategy": "trial_batch_runner",
+  "optimizer_requested_max_workers": "auto",
+  "optimizer_resolved_max_workers": 8,
   "diffraction_order": 1,
   "fourier_orders": 15,
   "angle_mode": "fixed",
   "grazing_angle_deg": 4.0,
-  "result_json_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit/best_result.json",
-  "trial_history_csv_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit/trial_history.csv",
-  "best_fit_plot_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit/best_fit.png",
-  "loss_history_plot_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit/optimization_loss_history.png"
+  "result_json_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit/best_result.json",
+  "trial_history_csv_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit/trial_history.csv",
+  "best_fit_plot_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit/best_fit.png",
+  "loss_history_plot_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit/optimization_loss_history.png"
 }
\ No newline at end of file
diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit/laminar_fit_measurement_comparison.png b/examples/optimizer/optimizer_laminar/results/laminar_fit/laminar_fit_measurement_comparison.png
index ce3883a..183be17 100644
Binary files a/examples/optimizer/optimizer_laminar/results/laminar_fit/laminar_fit_measurement_comparison.png and b/examples/optimizer/optimizer_laminar/results/laminar_fit/laminar_fit_measurement_comparison.png differ
diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit/optimization_loss_history.png b/examples/optimizer/optimizer_laminar/results/laminar_fit/optimization_loss_history.png
index 353f1b5..a165a56 100644
Binary files a/examples/optimizer/optimizer_laminar/results/laminar_fit/optimization_loss_history.png and b/examples/optimizer/optimizer_laminar/results/laminar_fit/optimization_loss_history.png differ
diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit/simulated_curve_fitted.csv b/examples/optimizer/optimizer_laminar/results/laminar_fit/simulated_curve_fitted.csv
index cbcdc76..30bce16 100644
--- a/examples/optimizer/optimizer_laminar/results/laminar_fit/simulated_curve_fitted.csv
+++ b/examples/optimizer/optimizer_laminar/results/laminar_fit/simulated_curve_fitted.csv
@@ -1,20 +1,20 @@
 case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
-fixed-00000000,51.031,4.0,-15,0.0001702013309866095,31.592684208420422
-fixed-00000000,51.031,4.0,-14,0.0002023328019795656,30.513240899031942
-fixed-00000000,51.031,4.0,-13,0.00016604453247059074,29.3981266579136
-fixed-00000000,51.031,4.0,-12,0.00013287173043563776,28.2430826673667
-fixed-00000000,51.031,4.0,-11,0.0003531019967483516,27.042958026955112
-fixed-00000000,51.031,4.0,-10,0.0003014228718815594,25.791424211271462
-fixed-00000000,51.031,4.0,-9,0.00012357678514677892,24.4805601660764
-fixed-00000000,51.031,4.0,-8,0.0006687045564903016,23.100228310925417
-fixed-00000000,51.031,4.0,-7,0.0007374825282471048,21.63709620023063
-fixed-00000000,51.031,4.0,-6,0.0001016523545541007,20.073021804562856
-fixed-00000000,51.031,4.0,-5,0.0015722981205339524,18.382209182495572
-fixed-00000000,51.031,4.0,-4,0.002560119512786236,16.52575062796602
-fixed-00000000,51.031,4.0,-3,9.038630067046438e-05,14.439839202533307
-fixed-00000000,51.031,4.0,-2,0.007998437837720158,12.005394489484559
-fixed-00000000,51.031,4.0,-1,0.03233722741114765,8.942057498804587
-fixed-00000000,51.031,4.0,0,0.7403398491130122,4.000000000000043
+fixed-00000000,51.031,4.0,-15,0.00016076079107510212,31.592684208420422
+fixed-00000000,51.031,4.0,-14,0.00012802322161001574,30.513240899031942
+fixed-00000000,51.031,4.0,-13,9.278666929974119e-05,29.3981266579136
+fixed-00000000,51.031,4.0,-12,0.0002021962007918016,28.2430826673667
+fixed-00000000,51.031,4.0,-11,0.0002679254721113848,27.042958026955112
+fixed-00000000,51.031,4.0,-10,0.00012246175772459661,25.791424211271462
+fixed-00000000,51.031,4.0,-9,0.00025757877039059925,24.4805601660764
+fixed-00000000,51.031,4.0,-8,0.0006446228982567493,23.100228310925417
+fixed-00000000,51.031,4.0,-7,0.0003509492528485857,21.63709620023063
+fixed-00000000,51.031,4.0,-6,0.00025233790996495267,20.073021804562856
+fixed-00000000,51.031,4.0,-5,0.0017330930929798302,18.382209182495572
+fixed-00000000,51.031,4.0,-4,0.0017801733126446228,16.52575062796602
+fixed-00000000,51.031,4.0,-3,0.00012689337696867884,14.439839202533307
+fixed-00000000,51.031,4.0,-2,0.008644173837772925,12.005394489484559
+fixed-00000000,51.031,4.0,-1,0.030007843235565428,8.942057498804587
+fixed-00000000,51.031,4.0,0,0.6941763900858002,4.000000000000043
 fixed-00000000,51.031,4.0,1,0.0,0.0
 fixed-00000000,51.031,4.0,2,0.0,0.0
 fixed-00000000,51.031,4.0,3,0.0,0.0
@@ -30,53 +30,270 @@ fixed-00000000,51.031,4.0,12,0.0,0.0
 fixed-00000000,51.031,4.0,13,0.0,0.0
 fixed-00000000,51.031,4.0,14,0.0,0.0
 fixed-00000000,51.031,4.0,15,0.0,0.0
-fixed-00000023,62.572,4.0,-15,0.0005146014451210195,28.51643518243408
-fixed-00000023,62.572,4.0,-14,0.000368770320342158,27.550216737549185
-fixed-00000023,62.572,4.0,-13,0.00036009930257008326,26.551699157895627
-fixed-00000023,62.572,4.0,-12,0.00031071791440573983,25.517071263566763
-fixed-00000023,62.572,4.0,-11,0.0005785675973605386,24.441727411335123
-fixed-00000023,62.572,4.0,-10,0.0005710815960067419,23.320014605275446
-fixed-00000023,62.572,4.0,-9,0.0002725633801770769,22.144865712484787
-fixed-00000023,62.572,4.0,-8,0.001030617313887299,20.90724903918249
-fixed-00000023,62.572,4.0,-7,0.001264887650822547,19.59530762873507
-fixed-00000023,62.572,4.0,-6,0.00023295958312673245,18.192943369650507
-fixed-00000023,62.572,4.0,-5,0.002322635986293163,16.67733340192183
-fixed-00000023,62.572,4.0,-4,0.004096626817328317,15.014191236263258
-fixed-00000023,62.572,4.0,-3,0.00023847168890673738,13.147613465698157
-fixed-00000023,62.572,4.0,-2,0.011631494106697131,10.97424015986465
-fixed-00000023,62.572,4.0,-1,0.04900961536263806,8.25515978716389
-fixed-00000023,62.572,4.0,0,0.754320365987236,4.000000000000128
-fixed-00000023,62.572,4.0,1,0.0,0.0
-fixed-00000023,62.572,4.0,2,0.0,0.0
-fixed-00000023,62.572,4.0,3,0.0,0.0
-fixed-00000023,62.572,4.0,4,0.0,0.0
-fixed-00000023,62.572,4.0,5,0.0,0.0
-fixed-00000023,62.572,4.0,6,0.0,0.0
-fixed-00000023,62.572,4.0,7,0.0,0.0
-fixed-00000023,62.572,4.0,8,0.0,0.0
-fixed-00000023,62.572,4.0,9,0.0,0.0
-fixed-00000023,62.572,4.0,10,0.0,0.0
-fixed-00000023,62.572,4.0,11,0.0,0.0
-fixed-00000023,62.572,4.0,12,0.0,0.0
-fixed-00000023,62.572,4.0,13,0.0,0.0
-fixed-00000023,62.572,4.0,14,0.0,0.0
-fixed-00000023,62.572,4.0,15,0.0,0.0
-fixed-00000012,57.074,4.0,-15,0.0003221771762076547,29.861904780911956
-fixed-00000012,57.074,4.0,-14,0.0002810219219934914,28.846303471443008
-fixed-00000012,57.074,4.0,-13,0.0002724201132310969,27.79690883296884
-fixed-00000012,57.074,4.0,-12,0.00020969522900305654,26.709712861142364
-fixed-00000012,57.074,4.0,-11,0.0004695227019579326,25.579870114234566
-fixed-00000012,57.074,4.0,-10,0.0004506560019176916,24.40143044571255
-fixed-00000012,57.074,4.0,-9,0.0001868419329159378,23.16695102928655
-fixed-00000012,57.074,4.0,-8,0.0008602208328407971,21.866913531793358
-fixed-00000012,57.074,4.0,-7,0.0010275662201960055,20.488811596774894
-fixed-00000012,57.074,4.0,-6,0.00015673198818107203,19.015647371174055
-fixed-00000012,57.074,4.0,-5,0.0019737744307674917,17.423289009554622
-fixed-00000012,57.074,4.0,-4,0.003388376063825405,15.675415124230582
-fixed-00000012,57.074,4.0,-3,0.0001561117894469589,13.712642009190432
-fixed-00000012,57.074,4.0,-2,0.009924704554441277,11.424689755176985
-fixed-00000012,57.074,4.0,-1,0.041028994498621026,8.55443800821682
-fixed-00000012,57.074,4.0,0,0.7517536827387111,4.000000000000043
+fixed-00000001,51.535,4.0,-15,0.00016315212719009988,31.436421708706995
+fixed-00000001,51.535,4.0,-14,0.00012984903803605735,30.36275821356324
+fixed-00000001,51.535,4.0,-13,9.429794305575519e-05,29.253591196974362
+fixed-00000001,51.535,4.0,-12,0.00020325958883048045,28.104684382152477
+fixed-00000001,51.535,4.0,-11,0.00026981638587081824,26.910914314750777
+fixed-00000001,51.535,4.0,-10,0.00012408016924553387,25.66598646074098
+fixed-00000001,51.535,4.0,-9,0.0002577907222845418,24.362022719115586
+fixed-00000001,51.535,4.0,-8,0.0006457409438137902,22.988941118718657
+fixed-00000001,51.535,4.0,-7,0.00035320265735919653,21.533483385001645
+fixed-00000001,51.535,4.0,-6,0.0002521571190217371,19.977610201627357
+fixed-00000001,51.535,4.0,-5,0.0017331612185457006,18.295674988789102
+fixed-00000001,51.535,4.0,-4,0.0017857946478481287,16.449002142991787
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diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit/simulated_curve_initial.csv b/examples/optimizer/optimizer_laminar/results/laminar_fit/simulated_curve_initial.csv
index 981f0e6..b42d16d 100644
--- a/examples/optimizer/optimizer_laminar/results/laminar_fit/simulated_curve_initial.csv
+++ b/examples/optimizer/optimizer_laminar/results/laminar_fit/simulated_curve_initial.csv
@@ -1,20 +1,20 @@
 case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
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 fixed-00000000,51.031,4.0,1,0.0,0.0
 fixed-00000000,51.031,4.0,2,0.0,0.0
 fixed-00000000,51.031,4.0,3,0.0,0.0
@@ -30,115 +30,22 @@ fixed-00000000,51.031,4.0,12,0.0,0.0
 fixed-00000000,51.031,4.0,13,0.0,0.0
 fixed-00000000,51.031,4.0,14,0.0,0.0
 fixed-00000000,51.031,4.0,15,0.0,0.0
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 fixed-00000001,51.535,4.0,1,0.0,0.0
 fixed-00000001,51.535,4.0,2,0.0,0.0
 fixed-00000001,51.535,4.0,3,0.0,0.0
@@ -154,84 +61,22 @@ fixed-00000001,51.535,4.0,12,0.0,0.0
 fixed-00000001,51.535,4.0,13,0.0,0.0
 fixed-00000001,51.535,4.0,14,0.0,0.0
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diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit/trial_history.csv b/examples/optimizer/optimizer_laminar/results/laminar_fit/trial_history.csv
index 0abcaac..c826d35 100644
--- a/examples/optimizer/optimizer_laminar/results/laminar_fit/trial_history.csv
+++ b/examples/optimizer/optimizer_laminar/results/laminar_fit/trial_history.csv
@@ -1,21 +1,21 @@
 trial_index,loss,width_to_period_ratio,depth_nm,left_wall_angle_deg,right_wall_angle_deg,top_cap_thickness_nm
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diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/best_fit.png b/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/best_fit.png
index e870c6e..16461eb 100644
Binary files a/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/best_fit.png and b/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/best_fit.png differ
diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/best_result.json b/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/best_result.json
index 346002e..f36afaa 100644
--- a/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/best_result.json
+++ b/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/best_result.json
@@ -2,7 +2,7 @@
   "optimization_mode": "measurement_fit",
   "experiment_name": "laminar_fit_tied_walls",
   "objective_name": "loss",
-  "measurement_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_laminar/measured_alpha4deg_order1.csv",
+  "measurement_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_laminar/measured_alpha4deg_order1.csv",
   "evaluation_mode": "energy_only",
   "evaluation_case_mode": "energy_only",
   "evaluation_energies_ev": [
@@ -74,19 +74,19 @@
   "equality_constraints": {
     "right_wall_angle_deg": "left_wall_angle_deg"
   },
-  "best_loss": 4.210862085164015e-06,
+  "best_loss": 3.037882457503803e-05,
   "best_parameters": {
-    "width_to_period_ratio": 0.7399114631988724,
-    "depth_nm": 14.689456819086626,
-    "left_wall_angle_deg": 5.0,
-    "top_cap_thickness_nm": 0.3
+    "width_to_period_ratio": 0.716518444026963,
+    "depth_nm": 14.101266065245971,
+    "left_wall_angle_deg": 11.750359887995446,
+    "top_cap_thickness_nm": 0.9791163034504053
   },
   "best_grating_parameters": {
-    "width_to_period_ratio": 0.7399114631988724,
-    "depth_nm": 14.689456819086626,
-    "left_wall_angle_deg": 5.0,
-    "top_cap_thickness_nm": 0.3,
-    "right_wall_angle_deg": 5.0
+    "width_to_period_ratio": 0.716518444026963,
+    "depth_nm": 14.101266065245971,
+    "left_wall_angle_deg": 11.750359887995446,
+    "top_cap_thickness_nm": 0.9791163034504053,
+    "right_wall_angle_deg": 11.750359887995446
   },
   "best_solver_parameters": {
     "roughness_sigma_nm": null
@@ -96,6 +96,11 @@
   "early_stop_reason": null,
   "backend_requested": "auto",
   "backend_effective": "numba",
+  "solver": "rcwa",
+  "solver_options": null,
+  "optimizer_execution_strategy": "trial_batch_runner",
+  "optimizer_requested_max_workers": "auto",
+  "optimizer_resolved_max_workers": 8,
   "diffraction_order": 1,
   "fourier_orders": 15,
   "angle_mode": "fixed",
diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/fitted_parameters.json b/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/fitted_parameters.json
index 37bbccf..07245c2 100644
--- a/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/fitted_parameters.json
+++ b/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/fitted_parameters.json
@@ -2,7 +2,7 @@
   "optimization_mode": "measurement_fit",
   "experiment_name": "laminar_fit_tied_walls",
   "objective_name": "loss",
-  "measurement_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_laminar/measured_alpha4deg_order1.csv",
+  "measurement_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_laminar/measured_alpha4deg_order1.csv",
   "evaluation_mode": "energy_only",
   "evaluation_case_mode": "energy_only",
   "evaluation_energies_ev": [
@@ -74,19 +74,19 @@
   "equality_constraints": {
     "right_wall_angle_deg": "left_wall_angle_deg"
   },
-  "best_loss": 4.210862085164015e-06,
+  "best_loss": 3.037882457503803e-05,
   "best_parameters": {
-    "width_to_period_ratio": 0.7399114631988724,
-    "depth_nm": 14.689456819086626,
-    "left_wall_angle_deg": 5.0,
-    "top_cap_thickness_nm": 0.3
+    "width_to_period_ratio": 0.716518444026963,
+    "depth_nm": 14.101266065245971,
+    "left_wall_angle_deg": 11.750359887995446,
+    "top_cap_thickness_nm": 0.9791163034504053
   },
   "best_grating_parameters": {
-    "width_to_period_ratio": 0.7399114631988724,
-    "depth_nm": 14.689456819086626,
-    "left_wall_angle_deg": 5.0,
-    "top_cap_thickness_nm": 0.3,
-    "right_wall_angle_deg": 5.0
+    "width_to_period_ratio": 0.716518444026963,
+    "depth_nm": 14.101266065245971,
+    "left_wall_angle_deg": 11.750359887995446,
+    "top_cap_thickness_nm": 0.9791163034504053,
+    "right_wall_angle_deg": 11.750359887995446
   },
   "best_solver_parameters": {
     "roughness_sigma_nm": null
@@ -96,12 +96,17 @@
   "early_stop_reason": null,
   "backend_requested": "auto",
   "backend_effective": "numba",
+  "solver": "rcwa",
+  "solver_options": null,
+  "optimizer_execution_strategy": "trial_batch_runner",
+  "optimizer_requested_max_workers": "auto",
+  "optimizer_resolved_max_workers": 8,
   "diffraction_order": 1,
   "fourier_orders": 15,
   "angle_mode": "fixed",
   "grazing_angle_deg": 4.0,
-  "result_json_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/best_result.json",
-  "trial_history_csv_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/trial_history.csv",
-  "best_fit_plot_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/best_fit.png",
-  "loss_history_plot_path": "/home/jny/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/optimization_loss_history.png"
+  "result_json_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/best_result.json",
+  "trial_history_csv_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/trial_history.csv",
+  "best_fit_plot_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/best_fit.png",
+  "loss_history_plot_path": "/Users/vadilonga/projects/graxPy/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/optimization_loss_history.png"
 }
\ No newline at end of file
diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/optimization_loss_history.png b/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/optimization_loss_history.png
index c8b9597..388d21e 100644
Binary files a/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/optimization_loss_history.png and b/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/optimization_loss_history.png differ
diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/simulated_curve_fitted.csv b/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/simulated_curve_fitted.csv
index 529b75c..defd7f2 100644
--- a/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/simulated_curve_fitted.csv
+++ b/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/simulated_curve_fitted.csv
@@ -1,20 +1,20 @@
 case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
-fixed-00000000,51.031,4.0,-15,4.076158139506949e-05,31.592684208420422
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-fixed-00000000,51.031,4.0,0,0.743418135493119,4.000000000000043
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 fixed-00000000,51.031,4.0,1,0.0,0.0
 fixed-00000000,51.031,4.0,2,0.0,0.0
 fixed-00000000,51.031,4.0,3,0.0,0.0
@@ -30,115 +30,22 @@ fixed-00000000,51.031,4.0,12,0.0,0.0
 fixed-00000000,51.031,4.0,13,0.0,0.0
 fixed-00000000,51.031,4.0,14,0.0,0.0
 fixed-00000000,51.031,4.0,15,0.0,0.0
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+fixed-00000778,649.744,4.0,-5,0.00017151922896992494,6.410344364265413
+fixed-00000778,649.744,4.0,-4,0.0013253030941212324,6.00595140898767
+fixed-00000778,649.744,4.0,-3,0.0012915711032275383,5.572402565576041
+fixed-00000778,649.744,4.0,-2,0.002315578762591102,5.10227088285194
+fixed-00000778,649.744,4.0,-1,0.012374450439013165,4.584315103889239
+fixed-00000778,649.744,4.0,0,0.23624255126381502,4.000000000000043
+fixed-00000778,649.744,4.0,1,0.008409824921028219,3.3144128387156258
+fixed-00000778,649.744,4.0,2,0.024197122711887304,2.443755631712577
+fixed-00000778,649.744,4.0,3,0.013289494939612232,0.9797073983953482
+fixed-00000778,649.744,4.0,4,0.0,0.0
+fixed-00000778,649.744,4.0,5,0.0,0.0
+fixed-00000778,649.744,4.0,6,0.0,0.0
+fixed-00000778,649.744,4.0,7,0.0,0.0
+fixed-00000778,649.744,4.0,8,0.0,0.0
+fixed-00000778,649.744,4.0,9,0.0,0.0
+fixed-00000778,649.744,4.0,10,0.0,0.0
+fixed-00000778,649.744,4.0,11,0.0,0.0
+fixed-00000778,649.744,4.0,12,0.0,0.0
+fixed-00000778,649.744,4.0,13,0.0,0.0
+fixed-00000778,649.744,4.0,14,0.0,0.0
+fixed-00000778,649.744,4.0,15,0.0,0.0
+fixed-00000779,651.725,4.0,-15,0.00023841820256140762,9.546947066051217
+fixed-00000779,651.725,4.0,-14,0.0001386057034805841,9.280390327923172
+fixed-00000779,651.725,4.0,-13,6.792144735847671e-05,9.006018631269328
+fixed-00000779,651.725,4.0,-12,0.00019806251566505107,8.723094539342426
+fixed-00000779,651.725,4.0,-11,0.00021992721720844022,8.430757031360244
+fixed-00000779,651.725,4.0,-10,8.986719464683698e-05,8.127990412317487
+fixed-00000779,651.725,4.0,-9,0.00014852727105463934,7.813582380901963
+fixed-00000779,651.725,4.0,-8,0.0002929701868515636,7.486066242159566
+fixed-00000779,651.725,4.0,-7,0.00030666400760706743,7.143639257338748
+fixed-00000779,651.725,4.0,-6,0.00011110230296018412,6.784043854115879
+fixed-00000779,651.725,4.0,-5,0.00018450117383848563,6.40438869291566
+fixed-00000779,651.725,4.0,-4,0.0013361792684718988,6.000867571202647
+fixed-00000779,651.725,4.0,-3,0.0012446308477674826,5.568294305154012
+fixed-00000779,651.725,4.0,-2,0.0023879541682434,5.099280668736824
+fixed-00000779,651.725,4.0,-1,0.012915475175779038,4.582651682225702
+fixed-00000779,651.725,4.0,0,0.2354416893406411,4.000000000000043
+fixed-00000779,651.725,4.0,1,0.007886432484268029,3.3167112087917303
+fixed-00000779,651.725,4.0,2,0.0238258234388835,2.4499827335566806
+fixed-00000779,651.725,4.0,3,0.013598233055907651,1.0027590358151457
 fixed-00000779,651.725,4.0,4,0.0,0.0
 fixed-00000779,651.725,4.0,5,0.0,0.0
 fixed-00000779,651.725,4.0,6,0.0,0.0
diff --git a/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/trial_history.csv b/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/trial_history.csv
index 9b0e2c5..ce7d16d 100644
--- a/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/trial_history.csv
+++ b/examples/optimizer/optimizer_laminar/results/laminar_fit_tied_walls/trial_history.csv
@@ -1,21 +1,21 @@
 trial_index,loss,width_to_period_ratio,depth_nm,left_wall_angle_deg,top_cap_thickness_nm
-0,0.0008135918844058124,0.559841938316822,14.24186440706253,16.240353882312775,0.6133334159851074
-1,0.00011678093951917602,0.7148598993197084,15.025467954203487,8.43977018725127,1.362469544634223
-2,0.00024458236717535075,0.7698737177997828,14.743462269753218,17.366110463626683,1.0935385241173208
-3,0.0011311552019339936,0.6148559023626149,15.52682929635048,10.064027272164822,1.626013820618391
-4,0.0011996592969765166,0.6042677959427237,14.630942705646158,6.088323965668678,1.7893493670970202
-5,0.00023822338849185782,0.758626503776759,15.69891643486917,13.903441769070923,0.8351596149615943
-6,0.00043528940051070105,0.6659845025278628,14.132273567467928,12.400081190280616,1.5224720999598502
-7,0.0005239548900766891,0.5116256505250931,15.20048381537199,19.71669835038483,0.35828627413138747
-8,0.00010060270433749945,0.7193277841807109,13.9,20.0,2.0
-9,0.00013005894852847878,0.7087138011650512,13.9,20.0,0.3
-10,0.00040207737225891264,0.7475374858360194,15.9,5.0,2.0
-11,0.00013715301844689182,0.7184473223709316,13.9,20.0,1.1855856934345452
-12,0.00024591542541030137,0.7115504525912043,15.9,20.0,1.2033968628722904
-13,0.00011669318375542982,0.722929610483886,13.9,5.0,0.3692828288476398
-14,0.0001318227769449174,0.7124378073435904,13.9,11.652152846368786,0.3
-15,0.00015360213423885118,0.7130290157461618,13.9,12.148954992986003,2.0
-16,0.0003773293248674279,0.7009477745036807,15.9,5.0,0.3
-17,7.933285415986269e-05,0.7336003960612312,14.591731341979663,20.0,0.3
-18,5.187862891422911e-05,0.7190006408376642,14.634353290263734,20.0,2.0
-19,4.210862085164015e-06,0.7399114631988724,14.689456819086626,5.0,0.3
+0,0.0008135918844068283,0.559841938316822,14.24186440706253,16.240353882312775,0.6133334159851074
+1,0.00011678093951943641,0.7148598993197084,15.025467954203487,8.43977018725127,1.362469544634223
+2,0.00024458236717584894,0.7698737177997828,14.743462269753218,17.366110463626683,1.0935385241173208
+3,0.001131155201932451,0.6148559023626149,15.52682929635048,10.064027272164822,1.626013820618391
+4,0.001199659296977716,0.6042677959427237,14.630942705646158,6.088323965668678,1.7893493670970202
+5,0.00023822338849185942,0.758626503776759,15.69891643486917,13.903441769070923,0.8351596149615943
+6,0.00043528940050921515,0.6659845025278628,14.132273567467928,12.400081190280616,1.5224720999598502
+7,0.0005239548900767254,0.5116256505250931,15.20048381537199,19.71669835038483,0.35828627413138747
+8,0.0001006027043381133,0.7193277864853607,13.9,20.0,2.0
+9,0.00023377698164013853,0.8,15.9,5.0,2.0
+10,0.00012874995771126532,0.707119760167294,13.9,20.0,0.3
+11,0.000466939310615543,0.7101018335314893,15.9,20.0,2.0
+12,0.00017223513524023312,0.7381753029866581,13.9,6.816608249648873,1.800797154024928
+13,0.0002045643995797525,0.7317735809641875,14.839818478131129,5.0,2.0
+14,3.037882457503803e-05,0.716518444026963,14.101266065245971,11.750359887995446,0.9791163034504053
+15,0.0003137224356373959,0.8,15.9,5.0,0.3
+16,0.000960809221249471,0.5,13.9,5.0,2.0
+17,8.311919513311606e-05,0.7237958284938073,13.9,14.128380917914034,0.9502774431357099
+18,0.0002304396644197308,0.708581942380681,14.090420449906748,5.0,1.1479949482849479
+19,7.065008586688768e-05,0.7189166691839592,14.525917441876372,14.415660429608765,2.0
diff --git a/examples/optimizer/optimizer_laminar/run_all.sh b/examples/optimizer/optimizer_laminar/run_all.sh
index 6c1f9f9..d839dc6 100755
--- a/examples/optimizer/optimizer_laminar/run_all.sh
+++ b/examples/optimizer/optimizer_laminar/run_all.sh
@@ -2,21 +2,22 @@
 set -euo pipefail
 
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+PYTHON_BIN="${PYTHON_BIN:-python}"
 
 echo "==> Running 0_fit_laminar_grating.py"
-python "${SCRIPT_DIR}/0_fit_laminar_grating.py"
+"${PYTHON_BIN}" "${SCRIPT_DIR}/0_fit_laminar_grating.py"
 
 echo "==> Running 0b_fit_laminar_grating_tied_walls.py"
-python "${SCRIPT_DIR}/0b_fit_laminar_grating_tied_walls.py"
+"${PYTHON_BIN}" "${SCRIPT_DIR}/0b_fit_laminar_grating_tied_walls.py"
 
 echo "==> Running 1_run_simulation_design_parameters.py"
-python "${SCRIPT_DIR}/1_run_simulation_design_parameters.py"
+"${PYTHON_BIN}" "${SCRIPT_DIR}/1_run_simulation_design_parameters.py"
 
 echo "==> Running 2_run_simulation_fitted_parameters.py"
-python "${SCRIPT_DIR}/2_run_simulation_fitted_parameters.py"
+"${PYTHON_BIN}" "${SCRIPT_DIR}/2_run_simulation_fitted_parameters.py"
 
 echo "==> Running 2b_run_simulation_tied_wall_fitted_parameters.py"
-python "${SCRIPT_DIR}/2b_run_simulation_tied_wall_fitted_parameters.py"
+"${PYTHON_BIN}" "${SCRIPT_DIR}/2b_run_simulation_tied_wall_fitted_parameters.py"
 
 echo "==> Running 3_plot_laminar_fit_comparison.py"
-python "${SCRIPT_DIR}/3_plot_laminar_fit_comparison.py"
+"${PYTHON_BIN}" "${SCRIPT_DIR}/3_plot_laminar_fit_comparison.py"
diff --git a/examples/optimizer/run_all.sh b/examples/optimizer/run_all.sh
index 89fe155..41a1ec2 100755
--- a/examples/optimizer/run_all.sh
+++ b/examples/optimizer/run_all.sh
@@ -3,11 +3,12 @@
 set -euo pipefail
 
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+PYTHON_BIN="${PYTHON_BIN:-python}"
 
 echo "==> Running blazed optimizer workflow"
-bash "${SCRIPT_DIR}/optimizer_blazed/run_all.sh"
+PYTHON_BIN="${PYTHON_BIN}" bash "${SCRIPT_DIR}/optimizer_blazed/run_all.sh"
 
 echo "==> Running laminar optimizer workflow"
-bash "${SCRIPT_DIR}/optimizer_laminar/run_all.sh"
+PYTHON_BIN="${PYTHON_BIN}" bash "${SCRIPT_DIR}/optimizer_laminar/run_all.sh"
 
 echo "==> All optimizer workflows completed"
diff --git a/examples/run_all.sh b/examples/run_all.sh
index 699eba6..bacea81 100755
--- a/examples/run_all.sh
+++ b/examples/run_all.sh
@@ -1,16 +1,67 @@
-#!/bin/bash
-# Curated examples runner only.
-# This script does not copy assets into docs; docs-sync ownership is:
-# docs/tutorials/assets/gratings/scripts/run_all.sh
+#!/usr/bin/env bash
+# Run every example group. Tutorial-image synchronization is handled by
+# tools/build_docs.sh.
 set -euo pipefail
 
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
 PYTHON_BIN="${PYTHON_BIN:-python}"
 
-echo "Running grating examples..."
-bash "$SCRIPT_DIR/grating/run_all.sh"
+run_grating=false
+run_optimizer=false
+run_simulations=false
 
-echo "Running optimizer examples..."
-bash "$SCRIPT_DIR/optimizer/run_all.sh"
+if [[ $# -eq 0 ]]; then
+    run_grating=true
+    run_optimizer=true
+    run_simulations=true
+fi
 
-echo "All curated examples completed."
+while [[ $# -gt 0 ]]; do
+    case "$1" in
+        --grating)
+            run_grating=true
+            ;;
+        --optimizer)
+            run_optimizer=true
+            ;;
+        --simulations)
+            run_simulations=true
+            ;;
+        --all)
+            run_grating=true
+            run_optimizer=true
+            run_simulations=true
+            ;;
+        -h|--help)
+            cat <<'EOF'
+Usage: ./run_all.sh [--grating] [--optimizer] [--simulations] [--all]
+
+With no options, runs all example groups.  Specify one or more group options
+to run only those groups.
+EOF
+            exit 0
+            ;;
+        *)
+            echo "Unknown option: $1" >&2
+            exit 1
+            ;;
+    esac
+    shift
+done
+
+if [[ "$run_grating" == true ]]; then
+    echo "Running grating examples..."
+    PYTHON_BIN="${PYTHON_BIN}" bash "$SCRIPT_DIR/grating/run_all.sh"
+fi
+
+if [[ "$run_optimizer" == true ]]; then
+    echo "Running optimizer examples..."
+    PYTHON_BIN="${PYTHON_BIN}" bash "$SCRIPT_DIR/optimizer/run_all.sh"
+fi
+
+if [[ "$run_simulations" == true ]]; then
+    echo "Running simulation examples..."
+    PYTHON_BIN="${PYTHON_BIN}" bash "$SCRIPT_DIR/simulation/run_all.sh"
+fi
+
+echo "Selected example groups completed."
diff --git a/examples/simulation/batch_user_cases/batch_user_cases.py b/examples/simulation/batch_user_cases/batch_user_cases.py
index bddfd68..46e6f2b 100644
--- a/examples/simulation/batch_user_cases/batch_user_cases.py
+++ b/examples/simulation/batch_user_cases/batch_user_cases.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import argparse
 from pathlib import Path
 
 import matplotlib.pyplot as plt
@@ -17,7 +18,7 @@
     left_wall_angle_deg=15.0,
     right_wall_angle_deg=15.0,
     x_resolution_nm=0.5,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
 )
 
 energy_ev = 1000.0
@@ -56,63 +57,76 @@
         }
     )
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=diffraction_order,
-    default_fourier_orders=25,
-    show_progress=True,
-    live_plot=False,
-    on_error="continue",
-    checkpoint_dir=checkpoint_dir,
-    checkpoint_interval=1,
-    resume=False,
-    backend="numba",
+parser = argparse.ArgumentParser(description="Batch runner over user-defined cases")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
 )
+args = parser.parse_args()
 
-results = list(runner.run_cases(user_cases))
+if __name__ == "__main__":
+    runner = grax.BatchSimulationRunner(
+        solver=args.solver,
+        diffraction_order=diffraction_order,
+        fourier_orders=15,
+        show_progress=True,
+        live_plot=True,
+        max_workers="auto",
+        on_error="continue",
+        checkpoint_dir=checkpoint_dir,
+        checkpoint_interval=1,
+        resume=False,
+        backend="numba",
+    )
 
-csv_path = output_dir / "batch_user_cases_all_orders.csv"
-grax.write_all_orders_csv(results, csv_path)
+    results = list(runner.run_cases(user_cases))
 
-orders_plot_path = output_dir / "batch_user_cases_orders_1_3_vs_depth.png"
-depth_values = np.asarray([float(result.case_data["depth_nm"]) for result in results], dtype=float)
-figure, axis = plt.subplots(figsize=(10, 6))
-markers = ["o", "s", "^"]
-for index, order in enumerate([1, 2, 3]):
-    order_efficiency = np.asarray(
-        [
-            grax.efficiency_for_order(
-                result.orders,
-                result.efficiency_all,
-                diffraction_order=order,
-            )
-            for result in results
-        ],
-        dtype=float,
-    )
-    axis.plot(
-        depth_values,
-        order_efficiency,
-        f"{markers[index]}-",
-        linewidth=1.0,
-        markersize=3.0,
-        label=f"Order {order}",
-    )
-axis.set_xlabel("Grating Depth (nm)")
-axis.set_ylabel("Diffraction Efficiency")
-axis.set_title("Batch User Cases: Orders 1-3 Efficiency vs Depth at 1000 eV")
-axis.grid(True, alpha=0.3)
-axis.legend(loc="best")
-figure.tight_layout()
-figure.savefig(orders_plot_path, dpi=150, bbox_inches="tight")
-plt.close(figure)
+    csv_path = output_dir / f"batch_user_cases_all_orders_{args.solver}.csv"
+    grax.write_all_orders_csv(results, csv_path)
+
+    orders_plot_path = output_dir / f"batch_user_cases_orders_1_3_vs_depth_{args.solver}.png"
+    depth_values = np.asarray([float(result.case_data["depth_nm"]) for result in results], dtype=float)
+    figure, axis = plt.subplots(figsize=(10, 6))
+    markers = ["o", "s", "^"]
+    for index, order in enumerate([1, 2, 3]):
+        order_efficiency = np.asarray(
+            [
+                grax.efficiency_for_order(
+                    result.orders,
+                    result.efficiency_all,
+                    diffraction_order=order,
+                )
+                for result in results
+            ],
+            dtype=float,
+        )
+        axis.plot(
+            depth_values,
+            order_efficiency,
+            f"{markers[index]}-",
+            linewidth=1.0,
+            markersize=3.0,
+            label=f"Order {order}",
+        )
+    axis.set_xlabel("Grating Depth (nm)")
+    axis.set_ylabel("Diffraction Efficiency")
+    axis.set_title("Batch User Cases: Orders 1-3 Efficiency vs Depth at 1000 eV")
+    axis.grid(True, alpha=0.3)
+    axis.legend(loc="best")
+    figure.tight_layout()
+    figure.savefig(orders_plot_path, dpi=150, bbox_inches="tight")
+    plt.close(figure)
 
-profile_grating = grax.LaminarGrating(depth_nm=depths_nm[0], **base_grating_kwargs)
-profile_path = output_dir / "batch_user_cases_profile.png"
-profile_grating.plot_profile(profile_path)
+    profile_grating = grax.LaminarGrating(depth_nm=depths_nm[0], **base_grating_kwargs)
+    profile_path = output_dir / "batch_user_cases_profile.png"
+    profile_grating.plot_profile(profile_path)
 
-print(f"Results saved to: {csv_path}")
-print(f"Orders 1-3 plot saved to: {orders_plot_path}")
-print(f"Profile plot saved to: {profile_path}")
-print(f"Energy: {energy_ev:.1f} eV")
-print(f"Monochromator grazing angle (cff={cff}): {grazing_angle_deg:.6f} deg")
-print(f"Checkpoint directory: {checkpoint_dir}")
+    print(f"Results saved to: {csv_path}")
+    print(f"Orders 1-3 plot saved to: {orders_plot_path}")
+    print(f"Profile plot saved to: {profile_path}")
+    print(f"Energy: {energy_ev:.1f} eV")
+    print(f"Monochromator grazing angle (cff={cff}): {grazing_angle_deg:.6f} deg")
+    print(f"Checkpoint directory: {checkpoint_dir}")
diff --git a/examples/simulation/batch_user_cases/polarization_comparison.py b/examples/simulation/batch_user_cases/polarization_comparison.py
index 17f94e8..47bf181 100644
--- a/examples/simulation/batch_user_cases/polarization_comparison.py
+++ b/examples/simulation/batch_user_cases/polarization_comparison.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import argparse
 from pathlib import Path
 
 import matplotlib.pyplot as plt
@@ -17,7 +18,7 @@
     left_wall_angle_deg=15.0,
     right_wall_angle_deg=15.0,
     x_resolution_nm=0.5,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
 )
 
 energy_ev = 1000.0
@@ -49,47 +50,60 @@
     cases_s.append({**base, "case_id": f"pol-s-depth-{int(depth_nm):03d}", "polarization": "s"})
     cases_p.append({**base, "case_id": f"pol-p-depth-{int(depth_nm):03d}", "polarization": "p"})
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=diffraction_order,
-    default_fourier_orders=25,
-    show_progress=True,
-    live_plot=False,
-    on_error="continue",
-    backend="numba",
+parser = argparse.ArgumentParser(description="Polarization comparison (s vs p)")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
 )
+args = parser.parse_args()
 
-results_s_by_id = {r.case_id: r for r in runner.run_cases(cases_s)}
-results_p_by_id = {r.case_id: r for r in runner.run_cases(cases_p)}
+if __name__ == "__main__":
+    runner = grax.BatchSimulationRunner(
+        solver=args.solver,
+        diffraction_order=diffraction_order,
+        fourier_orders=15,
+        show_progress=True,
+        live_plot=True,
+        max_workers="auto",
+        on_error="continue",
+        backend="numba",
+    )
 
-ordered_s = [results_s_by_id[f"pol-s-depth-{int(d):03d}"] for d in depths_nm]
-ordered_p = [results_p_by_id[f"pol-p-depth-{int(d):03d}"] for d in depths_nm]
+    results_s_by_id = {r.case_id: r for r in runner.run_cases(cases_s)}
+    results_p_by_id = {r.case_id: r for r in runner.run_cases(cases_p)}
 
-diffraction_orders = [1, 2, 3]
-colors = ["tab:blue", "tab:orange", "tab:green"]
-markers = ["o", "s", "^"]
+    ordered_s = [results_s_by_id[f"pol-s-depth-{int(d):03d}"] for d in depths_nm]
+    ordered_p = [results_p_by_id[f"pol-p-depth-{int(d):03d}"] for d in depths_nm]
 
-comparison_plot_path = output_dir / "batch_user_cases_pol_comparison.png"
-figure, axis = plt.subplots(figsize=(10, 6))
-for index, order in enumerate(diffraction_orders):
-    eff_s = np.asarray(
-        [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in ordered_s],
-        dtype=float,
-    )
-    eff_p = np.asarray(
-        [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in ordered_p],
-        dtype=float,
-    )
-    axis.plot(depths_nm, eff_s, f"{markers[index]}-", color=colors[index], linewidth=1.5, markersize=4, label=f"Order {order} (s)")
-    axis.plot(depths_nm, eff_p, f"{markers[index]}--", color=colors[index], linewidth=1.5, markersize=4, label=f"Order {order} (p)")
+    diffraction_orders = [1, 2, 3]
+    colors = ["tab:blue", "tab:orange", "tab:green"]
+    markers = ["o", "s", "^"]
+
+    comparison_plot_path = output_dir / f"batch_user_cases_pol_comparison_{args.solver}.png"
+    figure, axis = plt.subplots(figsize=(10, 6))
+    for index, order in enumerate(diffraction_orders):
+        eff_s = np.asarray(
+            [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in ordered_s],
+            dtype=float,
+        )
+        eff_p = np.asarray(
+            [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in ordered_p],
+            dtype=float,
+        )
+        axis.plot(depths_nm, eff_s, f"{markers[index]}-", color=colors[index], linewidth=1.5, markersize=4, label=f"Order {order} (s)")
+        axis.plot(depths_nm, eff_p, f"{markers[index]}--", color=colors[index], linewidth=1.5, markersize=4, label=f"Order {order} (p)")
 
-axis.set_xlabel("Grating Depth (nm)")
-axis.set_ylabel("Diffraction Efficiency")
-axis.set_title(f"Depth Sweep: s vs p Polarization, Orders 1–3 at {energy_ev:.0f} eV")
-axis.grid(True, alpha=0.3)
-axis.legend(loc="best")
-figure.tight_layout()
-figure.savefig(comparison_plot_path, dpi=150, bbox_inches="tight")
-plt.close(figure)
+    axis.set_xlabel("Grating Depth (nm)")
+    axis.set_ylabel("Diffraction Efficiency")
+    axis.set_title(f"Depth Sweep: s vs p Polarization, Orders 1–3 at {energy_ev:.0f} eV")
+    axis.grid(True, alpha=0.3)
+    axis.legend(loc="best")
+    figure.tight_layout()
+    figure.savefig(comparison_plot_path, dpi=150, bbox_inches="tight")
+    plt.close(figure)
 
-print(f"Polarization comparison plot saved to: {comparison_plot_path}")
-print(f"Energy: {energy_ev:.1f} eV, grazing angle (cff={cff}): {grazing_angle_deg:.6f} deg")
+    print(f"Polarization comparison plot saved to: {comparison_plot_path}")
+    print(f"Energy: {energy_ev:.1f} eV, grazing angle (cff={cff}): {grazing_angle_deg:.6f} deg")
diff --git a/examples/simulation/batch_user_cases/results/batch_user_cases_all_orders.csv b/examples/simulation/batch_user_cases/results/batch_user_cases_all_orders.csv
deleted file mode 100644
index 3b5e5de..0000000
--- a/examples/simulation/batch_user_cases/results/batch_user_cases_all_orders.csv
+++ /dev/null
@@ -1,232 +0,0 @@
-case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
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diff --git a/examples/simulation/batch_user_cases/results/batch_user_cases_all_orders_rcwa.csv b/examples/simulation/batch_user_cases/results/batch_user_cases_all_orders_rcwa.csv
new file mode 100644
index 0000000..a26cd83
--- /dev/null
+++ b/examples/simulation/batch_user_cases/results/batch_user_cases_all_orders_rcwa.csv
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diff --git a/examples/simulation/batch_user_cases/results/batch_user_cases_orders_1_3_vs_depth.png b/examples/simulation/batch_user_cases/results/batch_user_cases_orders_1_3_vs_depth.png
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diff --git a/examples/simulation/batch_user_cases/results/batch_user_cases_orders_1_3_vs_depth_rcwa.png b/examples/simulation/batch_user_cases/results/batch_user_cases_orders_1_3_vs_depth_rcwa.png
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diff --git a/examples/simulation/batch_user_cases/results/batch_user_cases_pol_comparison_rcwa.png b/examples/simulation/batch_user_cases/results/batch_user_cases_pol_comparison_rcwa.png
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diff --git a/examples/simulation/batch_user_cases/results/batch_user_cases_profile.png b/examples/simulation/batch_user_cases/results/batch_user_cases_profile.png
index a164fdf..6252855 100644
Binary files a/examples/simulation/batch_user_cases/results/batch_user_cases_profile.png and b/examples/simulation/batch_user_cases/results/batch_user_cases_profile.png differ
diff --git a/examples/simulation/batch_user_cases/results/checkpoints_depth_sweep/metadata.json b/examples/simulation/batch_user_cases/results/checkpoints_depth_sweep/metadata.json
index 7eaddd4..d452351 100644
--- a/examples/simulation/batch_user_cases/results/checkpoints_depth_sweep/metadata.json
+++ b/examples/simulation/batch_user_cases/results/checkpoints_depth_sweep/metadata.json
@@ -1,6 +1,8 @@
 {
-  "created": "2026-05-07T07:58:09.789847",
+  "created": "2026-08-17T10:16:56.015830",
   "execution_mode": "inline",
-  "default_diffraction_order": 1,
-  "default_fourier_orders": 5
-}
+  "max_workers": "auto",
+  "resolved_max_workers": 8,
+  "diffraction_order": 1,
+  "fourier_orders": 15
+}
\ No newline at end of file
diff --git a/examples/simulation/batch_user_cases/results/checkpoints_depth_sweep/results.jsonl b/examples/simulation/batch_user_cases/results/checkpoints_depth_sweep/results.jsonl
index fc0e230..ee0154e 100644
--- a/examples/simulation/batch_user_cases/results/checkpoints_depth_sweep/results.jsonl
+++ b/examples/simulation/batch_user_cases/results/checkpoints_depth_sweep/results.jsonl
@@ -145,3 +145,45 @@
 {"case_id": "user-laminar-depth-028", "index": 18, "label": "Laminar grating at depth 28.0 nm", "energy_ev": 1000.0, "grazing_angle_deg": 0.8951257766459548, "orders": [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5], "selected_efficiency": 0.09082218613937373, "selected_diffraction_angle_deg": 2.01436601556118, "efficiency_all": [0.003324459582509146, 0.0038810973344213595, 0.005284997206240286, 0.014770530044870571, 0.09082218613937373, 0.34644767939107635, 0.0, 0.0, 0.0, 0.0, 0.0], "diffraction_angle_all": [4.133852781071724, 3.718892740125014, 3.2514807025524135, 2.7045571247570592, 2.01436601556118, 0.8951257766461254, 0.0, 0.0, 0.0, 0.0, 0.0], "status": "ok", "error_message": null, "case_data": {"case_id": "user-laminar-depth-028", "label": "Laminar grating at depth 28.0 nm", "energy_ev": 1000.0, "grazing_angle_deg": 0.8951257766459548, "diffraction_order": 1, "depth_nm": 28.0}, "timestamp": "2026-05-07T08:00:01.640365"}
 {"case_id": "user-laminar-depth-029", "index": 19, "label": "Laminar grating at depth 29.0 nm", "energy_ev": 1000.0, "grazing_angle_deg": 0.8951257766459548, "orders": [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5], "selected_efficiency": 0.09312856793131767, "selected_diffraction_angle_deg": 2.01436601556118, "efficiency_all": [0.004063193930734966, 0.003978627191867749, 0.006070667179948905, 0.018747225769099866, 0.09312856793131767, 0.3439837279459393, 0.0, 0.0, 0.0, 0.0, 0.0], "diffraction_angle_all": [4.133852781071724, 3.718892740125014, 3.2514807025524135, 2.7045571247570592, 2.01436601556118, 0.8951257766461254, 0.0, 0.0, 0.0, 0.0, 0.0], "status": "ok", "error_message": null, "case_data": {"case_id": "user-laminar-depth-029", "label": "Laminar grating at depth 29.0 nm", "energy_ev": 1000.0, "grazing_angle_deg": 0.8951257766459548, "diffraction_order": 1, "depth_nm": 29.0}, "timestamp": "2026-05-07T08:00:10.246992"}
 {"case_id": "user-laminar-depth-030", "index": 20, "label": "Laminar grating at depth 30.0 nm", "energy_ev": 1000.0, "grazing_angle_deg": 0.8951257766459548, "orders": [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5], "selected_efficiency": 0.09360540666823465, "selected_diffraction_angle_deg": 2.01436601556118, "efficiency_all": [0.005057884525405065, 0.004912890564292692, 0.007206031007260576, 0.022649395438514474, 0.09360540666823465, 0.3403299983749495, 0.0, 0.0, 0.0, 0.0, 0.0], "diffraction_angle_all": [4.133852781071724, 3.718892740125014, 3.2514807025524135, 2.7045571247570592, 2.01436601556118, 0.8951257766461254, 0.0, 0.0, 0.0, 0.0, 0.0], "status": "ok", "error_message": null, "case_data": {"case_id": "user-laminar-depth-030", "label": "Laminar grating at depth 30.0 nm", "energy_ev": 1000.0, "grazing_angle_deg": 0.8951257766459548, "diffraction_order": 1, "depth_nm": 30.0}, "timestamp": "2026-05-07T08:00:17.268566"}
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+{"case_id": "user-laminar-depth-026", "index": 16, "label": "Laminar grating at depth 26.0 nm", "energy_ev": 1000.0, "grazing_angle_deg": 0.8951257766459548, "orders": [-15.0, -14.0, -13.0, -12.0, -11.0, -10.0, -9.0, -8.0, -7.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0], "selected_efficiency": 0.08790313443861507, "selected_diffraction_angle_deg": 2.014366015561194, "efficiency_all": [5.139932134899307e-05, 0.00011003448634538981, 7.696759546956603e-05, 9.532204329278562e-05, 0.0002319895235584569, 0.00014539959437797928, 0.00019835294971172086, 0.00043036894615345754, 0.0005327436541615674, 0.0009461749702113079, 0.0033793531285959736, 0.006444184926033487, 0.0033461139357120816, 0.013731313461911587, 0.08790313443861507, 0.34352880260249624, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "diffraction_angle_all": [7.050120230132293, 6.814705889326206, 6.5709039526000765, 6.317743444674818, 6.054050427444366, 5.778383128096706, 5.488937694018816, 5.183406473007082, 4.858755841479493, 4.51085953919187, 4.133852781071724, 3.718892740125014, 3.2514807025524135, 2.7045571247570592, 2.014366015561194, 0.8951257766461254, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "status": "ok", "error_message": null, "peak_memory_bytes": null, "wall_seconds": null, "case_data": {"case_id": "user-laminar-depth-026", "label": "Laminar grating at depth 26.0 nm", "energy_ev": 1000.0, "grazing_angle_deg": 0.8951257766459548, "diffraction_order": 1, "depth_nm": 26.0}, "polarization": "s", "solver": "rcwa", "solver_options": null, "theta_search_diagnostics": null, "retry_triggered": false, "retry_attempts": 0, "retry_status": "not_needed", "selected_efficiency_is_exact_zero": false, "selected_efficiency_below_retry_threshold": false, "theta_tracking_center_mode": "bragg", "theta_tracking_auto_classification": "initial", "theta_tracking_previous_energy_ev": null, "theta_tracking_previous_grazing_angle_deg": null, "theta_tracking_used_previous_theta": false, "theta_tracking_bragg_fallback_triggered": false, "theta_tracking_continuity_rejected": false, "timestamp": "2026-08-17T10:16:59.248176"}
+{"case_id": "user-laminar-depth-025", "index": 15, "label": "Laminar grating at depth 25.0 nm", "energy_ev": 1000.0, "grazing_angle_deg": 0.8951257766459548, "orders": [-15.0, -14.0, -13.0, -12.0, -11.0, -10.0, -9.0, -8.0, -7.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0], "selected_efficiency": 0.08025652615114043, "selected_diffraction_angle_deg": 2.014366015561194, "efficiency_all": [6.48435922646561e-05, 0.00011216431389111867, 7.188948937525244e-05, 9.441766800917668e-05, 0.0002040178053773194, 0.00011854513722065001, 0.0001722785783715809, 0.000479866826037462, 0.0004969116941429862, 0.0013800434575790548, 0.003637174023131622, 0.00733040640600063, 0.005035437007035449, 0.012677729665935368, 0.08025652615114043, 0.3422094726910698, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "diffraction_angle_all": [7.050120230132293, 6.814705889326206, 6.5709039526000765, 6.317743444674818, 6.054050427444366, 5.778383128096706, 5.488937694018816, 5.183406473007082, 4.858755841479493, 4.51085953919187, 4.133852781071724, 3.718892740125014, 3.2514807025524135, 2.7045571247570592, 2.014366015561194, 0.8951257766461254, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "status": "ok", "error_message": null, "peak_memory_bytes": null, "wall_seconds": null, "case_data": {"case_id": "user-laminar-depth-025", "label": "Laminar grating at depth 25.0 nm", "energy_ev": 1000.0, "grazing_angle_deg": 0.8951257766459548, "diffraction_order": 1, "depth_nm": 25.0}, "polarization": "s", "solver": "rcwa", "solver_options": null, "theta_search_diagnostics": null, "retry_triggered": false, "retry_attempts": 0, "retry_status": "not_needed", "selected_efficiency_is_exact_zero": false, "selected_efficiency_below_retry_threshold": false, "theta_tracking_center_mode": "bragg", "theta_tracking_auto_classification": "initial", "theta_tracking_previous_energy_ev": null, "theta_tracking_previous_grazing_angle_deg": null, "theta_tracking_used_previous_theta": false, "theta_tracking_bragg_fallback_triggered": false, "theta_tracking_continuity_rejected": false, "timestamp": "2026-08-17T10:16:59.360919"}
+{"case_id": "user-laminar-depth-029", "index": 19, "label": "Laminar grating at depth 29.0 nm", "energy_ev": 1000.0, "grazing_angle_deg": 0.8951257766459548, "orders": [-15.0, -14.0, -13.0, -12.0, -11.0, -10.0, -9.0, -8.0, -7.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0], "selected_efficiency": 0.10042797253988789, "selected_diffraction_angle_deg": 2.014366015561194, "efficiency_all": [5.6200579961188534e-05, 0.00012990877719139582, 0.00010766815531049374, 0.00013910288116352206, 0.00031816278203094633, 0.00032950400507231675, 0.0003423736377538816, 0.0009393255590277638, 0.0008472550110221151, 0.0009217206577249907, 0.004041830126129522, 0.004610579845865377, 0.005346170097758563, 0.02477153504683768, 0.10042797253988789, 0.33560375148218297, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "diffraction_angle_all": [7.050120230132293, 6.814705889326206, 6.5709039526000765, 6.317743444674818, 6.054050427444366, 5.778383128096706, 5.488937694018816, 5.183406473007082, 4.858755841479493, 4.51085953919187, 4.133852781071724, 3.718892740125014, 3.2514807025524135, 2.7045571247570592, 2.014366015561194, 0.8951257766461254, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "status": "ok", "error_message": null, "peak_memory_bytes": null, "wall_seconds": null, "case_data": {"case_id": "user-laminar-depth-029", "label": "Laminar grating at depth 29.0 nm", "energy_ev": 1000.0, "grazing_angle_deg": 0.8951257766459548, "diffraction_order": 1, "depth_nm": 29.0}, "polarization": "s", "solver": "rcwa", "solver_options": null, "theta_search_diagnostics": null, "retry_triggered": false, "retry_attempts": 0, "retry_status": "not_needed", "selected_efficiency_is_exact_zero": false, "selected_efficiency_below_retry_threshold": false, "theta_tracking_center_mode": "bragg", "theta_tracking_auto_classification": "initial", "theta_tracking_previous_energy_ev": null, "theta_tracking_previous_grazing_angle_deg": null, "theta_tracking_used_previous_theta": false, "theta_tracking_bragg_fallback_triggered": false, "theta_tracking_continuity_rejected": false, "timestamp": "2026-08-17T10:16:59.474222"}
diff --git a/examples/simulation/blazed_multilayer_memory_comparison/blazed_multilayer_memory_comparison.py b/examples/simulation/blazed_multilayer_memory_comparison/blazed_multilayer_memory_comparison.py
index 459f745..3e18b3c 100644
--- a/examples/simulation/blazed_multilayer_memory_comparison/blazed_multilayer_memory_comparison.py
+++ b/examples/simulation/blazed_multilayer_memory_comparison/blazed_multilayer_memory_comparison.py
@@ -2,6 +2,8 @@
 
 from __future__ import annotations
 
+import argparse
+
 import csv
 import sys
 from pathlib import Path
@@ -50,97 +52,115 @@
     )
 ]
 
-runner = grax.BatchSimulationRunner(
-    show_progress=True,
-    default_fourier_orders=20,
-    max_workers="auto",
-    backend="numba",
+parser = argparse.ArgumentParser(description="Blazed multilayer low-memory sweep")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
 )
-
-results = list(runner.run_cases(cases))
-results_by_case_id = {result.case_id: result for result in results}
-
-csv_path = output_dir / "blazed_multilayer_memory_comparison.csv"
-plot_path = output_dir / "blazed_multilayer_memory_comparison.png"
-profile_plot_path = output_dir / "blazed_multilayer_profile.png"
-stack_plot_path = output_dir / "multilayer_stack_schematic.png"
-
-with csv_path.open("w", newline="", encoding="utf-8") as handle:
-    writer = csv.writer(handle)
-    writer.writerow(
-        [
-            "energy_ev",
-            "grazing_angle_deg",
-            "selected_efficiency",
-            "selected_diffraction_angle_deg",
-            "peak_memory_mb",
-            "wall_seconds",
-        ]
+args = parser.parse_args()
+
+# Guard the executable part: the batch runner spawns worker processes on macOS,
+# and a spawned worker re-imports this file by path. Without the guard each
+# worker re-runs the whole example and recursively spawns more, which fails with
+# BrokenProcessPool before any case completes.
+if __name__ == "__main__":
+    runner = grax.BatchSimulationRunner(
+        solver=args.solver,
+        show_progress=True,
+        fourier_orders=20,
+        max_workers="auto",
+        live_plot=True,
+        live_plot_x_key="energy_ev",
+        backend="numba",
     )
-    for case in cases:
-        result = results_by_case_id[case["case_id"]]
+
+    results = list(runner.run_cases(cases))
+    results_by_case_id = {result.case_id: result for result in results}
+
+    csv_path = output_dir / f"blazed_multilayer_memory_comparison_{args.solver}.csv"
+    plot_path = output_dir / f"blazed_multilayer_memory_comparison_{args.solver}.png"
+    profile_plot_path = output_dir / "blazed_multilayer_profile.png"
+    stack_plot_path = output_dir / "multilayer_stack_schematic.png"
+
+    with csv_path.open("w", newline="", encoding="utf-8") as handle:
+        writer = csv.writer(handle)
         writer.writerow(
             [
-                float(case["energy_ev"]),
-                float(case["grazing_angle_deg"]),
-                float(result.selected_efficiency),
-                float(result.selected_diffraction_angle_deg),
-                float(result.peak_memory_bytes or 0) / (1024.0 * 1024.0),
-                float(result.wall_seconds or 0.0),
+                "energy_ev",
+                "grazing_angle_deg",
+                "selected_efficiency",
+                "selected_diffraction_angle_deg",
+                "peak_memory_mb",
+                "wall_seconds",
             ]
         )
+        for case in cases:
+            result = results_by_case_id[case["case_id"]]
+            writer.writerow(
+                [
+                    float(case["energy_ev"]),
+                    float(case["grazing_angle_deg"]),
+                    float(result.selected_efficiency),
+                    float(result.selected_diffraction_angle_deg),
+                    float(result.peak_memory_bytes or 0) / (1024.0 * 1024.0),
+                    float(result.wall_seconds or 0.0),
+                ]
+            )
+
+    energy_values = np.asarray([float(case["energy_ev"]) for case in cases], dtype=float)
+    selected_efficiency = np.asarray(
+        [float(results_by_case_id[case["case_id"]].selected_efficiency) for case in cases],
+        dtype=float,
+    )
+    peak_memory_mb = np.asarray(
+        [float(results_by_case_id[case["case_id"]].peak_memory_bytes or 0) / (1024.0 * 1024.0) for case in cases],
+        dtype=float,
+    )
+    wall_seconds = np.asarray(
+        [float(results_by_case_id[case["case_id"]].wall_seconds or 0.0) for case in cases],
+        dtype=float,
+    )
+    max_peak_memory = float(np.max(peak_memory_mb))
+    max_wall_seconds = float(np.max(wall_seconds))
+
+    figure, axes = plt.subplots(2, 1, figsize=(10, 8), sharex=True)
+
+    efficiency_axis = axes[0]
+    efficiency_axis.plot(energy_values, selected_efficiency, marker="o", linewidth=1.8, color="tab:blue")
+    efficiency_axis.set_ylabel("Selected efficiency")
+    efficiency_axis.set_title("Blazed multilayer sweep with low-memory execution")
+    efficiency_axis.grid(True, alpha=0.3)
+
+    memory_axis = axes[1]
+    memory_axis.plot(energy_values, peak_memory_mb, marker="s", linewidth=1.8, color="tab:orange", label="Peak memory")
+    memory_axis.plot(energy_values, wall_seconds, marker="^", linewidth=1.8, color="tab:green", label="Wall seconds")
+    memory_axis.set_xlabel("Energy (eV)")
+    memory_axis.set_ylabel("Profiled cost")
+    memory_axis.grid(True, alpha=0.3)
+    memory_axis.legend(loc="best")
+    memory_axis.text(
+        0.01,
+        0.02,
+        f"max peak memory = {max_peak_memory:.2f} MB\nmax wall time = {max_wall_seconds:.2f} s",
+        transform=memory_axis.transAxes,
+        va="bottom",
+        ha="left",
+        bbox={"boxstyle": "round", "facecolor": "white", "alpha": 0.8},
+    )
 
-energy_values = np.asarray([float(case["energy_ev"]) for case in cases], dtype=float)
-selected_efficiency = np.asarray(
-    [float(results_by_case_id[case["case_id"]].selected_efficiency) for case in cases],
-    dtype=float,
-)
-peak_memory_mb = np.asarray(
-    [float(results_by_case_id[case["case_id"]].peak_memory_bytes or 0) / (1024.0 * 1024.0) for case in cases],
-    dtype=float,
-)
-wall_seconds = np.asarray(
-    [float(results_by_case_id[case["case_id"]].wall_seconds or 0.0) for case in cases],
-    dtype=float,
-)
-max_peak_memory = float(np.max(peak_memory_mb))
-max_wall_seconds = float(np.max(wall_seconds))
-
-figure, axes = plt.subplots(2, 1, figsize=(10, 8), sharex=True)
-
-efficiency_axis = axes[0]
-efficiency_axis.plot(energy_values, selected_efficiency, marker="o", linewidth=1.8, color="tab:blue")
-efficiency_axis.set_ylabel("Selected efficiency")
-efficiency_axis.set_title("Blazed multilayer sweep with low-memory execution")
-efficiency_axis.grid(True, alpha=0.3)
-
-memory_axis = axes[1]
-memory_axis.plot(energy_values, peak_memory_mb, marker="s", linewidth=1.8, color="tab:orange", label="Peak memory")
-memory_axis.plot(energy_values, wall_seconds, marker="^", linewidth=1.8, color="tab:green", label="Wall seconds")
-memory_axis.set_xlabel("Energy (eV)")
-memory_axis.set_ylabel("Profiled cost")
-memory_axis.grid(True, alpha=0.3)
-memory_axis.legend(loc="best")
-memory_axis.text(
-    0.01,
-    0.02,
-    f"max peak memory = {max_peak_memory:.2f} MB\nmax wall time = {max_wall_seconds:.2f} s",
-    transform=memory_axis.transAxes,
-    va="bottom",
-    ha="left",
-    bbox={"boxstyle": "round", "facecolor": "white", "alpha": 0.8},
-)
-
-figure.tight_layout()
-figure.savefig(plot_path, dpi=150, bbox_inches="tight")
-plt.close(figure)
+    figure.tight_layout()
+    figure.savefig(plot_path, dpi=150, bbox_inches="tight")
+    plt.close(figure)
 
-grating.plot_profile(profile_plot_path)
-multilayer_stack.plot_schematic(stack_plot_path)
+    grating.plot_profile(profile_plot_path)
+    multilayer_stack.plot_schematic(stack_plot_path)
 
-print(f"Results saved to: {csv_path}")
-print(f"Plot saved to: {plot_path}")
-print(f"Profile plot saved to: {profile_plot_path}")
-print(f"Stack schematic saved to: {stack_plot_path}")
-print(f"Max peak memory: {max_peak_memory:.3f} MB")
-print(f"Max wall time: {max_wall_seconds:.3f} s")
+    print(f"Results saved to: {csv_path}")
+    print(f"Plot saved to: {plot_path}")
+    print(f"Profile plot saved to: {profile_plot_path}")
+    print(f"Stack schematic saved to: {stack_plot_path}")
+    print(f"Max peak memory: {max_peak_memory:.3f} MB")
+    print(f"Max wall time: {max_wall_seconds:.3f} s")
diff --git a/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_memory_comparison.csv b/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_memory_comparison.csv
deleted file mode 100644
index 1942e3d..0000000
--- a/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_memory_comparison.csv
+++ /dev/null
@@ -1,51 +0,0 @@
-energy_ev,grazing_angle_deg,selected_efficiency,selected_diffraction_angle_deg,peak_memory_mb,wall_seconds
-3000.0,1.2657162233926442,0.04606413132220752,2.8488035246260353,30.94045639038086,7.333309312001802
-3010.204081632653,1.263570357825742,0.043528011922024094,2.8439705405147464,30.760047912597656,34.51984284503851
-3020.408163265306,1.2614353695268363,0.036659471736064576,2.839162070655334,30.75493621826172,33.808120432076976
-3030.612244897959,1.2593111669115444,0.028858081329716376,2.8343779085071787,30.755142211914062,33.63029039197136
-3040.816326530612,1.257197659471501,0.024978313330688076,2.8296178499580833,30.753971099853516,32.727205109084025
-3051.0204081632655,1.2550947577582718,0.029380373542972012,2.8248816932876366,30.759357452392578,32.47125195793342
-3061.2244897959185,1.2530023733671953,0.043589409230205,2.82016923913028,30.75640106201172,35.59635478898417
-3071.4285714285716,1.2509204189216234,0.06492765424347398,2.8154802904413714,30.757396697998047,32.2062557770405
-3081.6326530612246,1.2488488080581135,0.08717482553147052,2.81081465246163,30.759536743164062,33.663884530891664
-3091.8367346938776,1.2467874554110097,0.10303032573936509,2.8061721326836846,30.756507873535156,29.890339573961683
-3102.0408163265306,1.244736276597692,0.10703676628364106,2.8015525408186335,30.759078979492188,31.48584341001697
-3112.2448979591836,1.2426951882041237,0.09793143874687647,2.796955688762793,30.75845718383789,32.919375187018886
-3122.4489795918366,1.2406641077706269,0.08099799494002428,2.7923813905663906,30.75583267211914,33.27004550793208
-3132.6530612244896,1.2386429537777701,0.0709531508362042,2.7878294624010636,30.75621795654297,34.0124917490175
-3142.8571428571427,1.2366316456328121,0.08986111381006164,2.7832997225298612,30.760974884033203,34.54280814004596
-3153.0612244897957,1.2346301036561727,0.1511217700398534,2.7787919912759236,30.75647735595703,29.160996002028696
-3163.265306122449,1.2326382490680174,0.24286141038185968,2.7743060909923543,30.756366729736328,30.844522489001974
-3173.469387755102,1.230656003975227,0.33845687683341175,2.769841846033401,30.754405975341797,34.40758121502586
-3183.673469387755,1.2286832913589905,0.4189385461300582,2.7653990827263613,30.756431579589844,33.44487018301152
-3193.877551020408,1.2267200350616605,0.47900794351678294,2.7609776293410704,30.760055541992188,34.08887782099191
-3204.081632653061,1.224766159775001,0.5208456548995228,2.756577316063982,30.755001068115234,35.04528444597963
-3214.285714285714,1.2228215910274258,0.5485270249947822,2.75219797496986,30.756019592285156,27.94020194991026
-3224.4897959183672,1.2208862551725304,0.5656543796169249,2.7478394399949053,30.755081176757812,31.71745545102749
-3234.6938775510203,1.2189600793773963,0.5748130509727712,2.7435015469102098,30.752788543701172,27.921426816959865
-3244.8979591836733,1.2170429916107395,0.577910235614541,2.739184133296135,30.75662612915039,31.66138413490262
-3255.1020408163267,1.2151349206317406,0.5761978577400375,2.734887038517215,30.756961822509766,34.32379906391725
-3265.3061224489797,1.2132357959792444,0.5704506839800972,2.730610103695639,30.75430679321289,31.617136006010696
-3275.5102040816328,1.2113455479603203,0.5610355269834354,2.7263531716875775,30.752845764160156,14.257971282000653
-3285.714285714286,1.2094641076396897,0.5479113193708451,2.7221160870589074,30.753337860107422,17.588966976036318
-3295.918367346939,1.2075914068296498,0.5308738592907477,2.717898696061596,30.752952575683594,32.60973061004188
-3306.122448979592,1.2057273780788194,0.5094956533668098,2.7137008466090293,30.75263214111328,35.36590716300998
-3316.326530612245,1.2038719546625742,0.48317179136965355,2.7095223882545696,31.06951141357422,27.40163586498238
-3326.530612244898,1.202025070572816,0.4511062871504911,2.705363172167395,31.072071075439453,22.98592268093489
-3336.734693877551,1.2001866605082938,0.41227694573959006,2.7012230511118815,31.07571029663086,20.744605934014544
-3346.9387755102043,1.198356659864487,0.3657145642503755,2.697101879424281,31.07054901123047,20.42729388002772
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-3367.3469387755104,1.1947216318492622,0.24920939654490745,2.6889158092319576,31.04210662841797,16.310765904025175
-3377.5510204081634,1.1929164786689341,0.1845924549111949,2.68485062707056,31.038223266601562,20.453922603977844
-3387.7551020408164,1.191119483273141,0.12528309185076614,2.6808038269218883,31.037887573242188,13.05683225800749
-3397.9591836734694,1.1893305844025122,0.08144290688021794,2.6767752706687986,31.070785522460938,20.023671053000726
-3408.1632653061224,1.187549721439865,0.05941139020011669,2.6727648216428292,31.072769165039062,19.42579162796028
-3418.3673469387754,1.1857768344011674,0.05668757877461513,2.668772344603795,31.07097625732422,19.30209574906621
-3428.5714285714284,1.184011863927779,0.06377841563217865,2.6647977057224637,31.030475616455078,16.91482518997509
-3438.7755102040815,1.18225475127727,0.0706453866474241,2.6608407725598227,31.036579132080078,14.276144640054554
-3448.9795918367345,1.1805054383160325,0.071093974772367,2.6569014140504237,31.073223114013672,18.79679616901558
-3459.183673469388,1.1787638675105399,0.06348298183984888,2.6529795004816066,31.03594970703125,13.716087247943506
-3469.387755102041,1.1770299819197447,0.04970114266594582,2.649074903478379,31.039798736572266,15.50303018197883
-3479.591836734694,1.1753037251871348,0.03380212591977927,2.645187495983606,31.041019439697266,11.414796002907678
-3489.795918367347,1.1735850415331583,0.020358160998099385,2.641317152242152,31.069011688232422,11.015237292973325
-3500.0,1.171873875747508,0.012671046915749228,2.637463747782448,31.037261962890625,15.96680627099704
diff --git a/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_memory_comparison.png b/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_memory_comparison.png
deleted file mode 100644
index 621163f..0000000
Binary files a/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_memory_comparison.png and /dev/null differ
diff --git a/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_memory_comparison_rcwa.csv b/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_memory_comparison_rcwa.csv
new file mode 100644
index 0000000..c16deaa
--- /dev/null
+++ b/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_memory_comparison_rcwa.csv
@@ -0,0 +1,51 @@
+energy_ev,grazing_angle_deg,selected_efficiency,selected_diffraction_angle_deg,peak_memory_mb,wall_seconds
+3000.0,1.2657162233926442,0.08389686630573338,2.8488035246260353,99.96568012237549,2.2605537499985076
+3010.204081632653,1.263570357825742,0.08888448142927896,2.8439705405147464,99.96547985076904,2.5504238749999786
+3020.408163265306,1.2614353695268363,0.09377651417466978,2.839162070655334,99.96498394012451,2.5650063330031116
+3030.612244897959,1.2593111669114734,0.09850371575283555,2.834377908507051,99.96663856506348,2.545698166002694
+3040.816326530612,1.257197659471501,0.10304973526972958,2.8296178499580833,99.96597862243652,2.569908541998302
+3051.0204081632655,1.2550947577582718,0.10742496989841369,2.8248816932876366,99.96514320373535,2.5584430000017164
+3061.2244897959185,1.2530023733671953,0.11163686136678229,2.82016923913028,99.96539306640625,2.5487444999962463
+3071.4285714285716,1.2509204189216234,0.11563999184339956,2.8154802904413714,99.96628952026367,2.5501256250063307
+3081.6326530612246,1.2488488080581135,0.11936359053998051,2.81081465246163,99.96564674377441,2.5583963329991093
+3091.8367346938776,1.2467874554110097,0.12282992738605994,2.8061721326836846,85.01702308654785,2.0706596250020084
+3102.0408163265306,1.244736276597692,0.1260674021126362,2.8015525408186335,85.01910591125488,2.086460750004335
+3112.2448979591836,1.2426951882041237,0.12907702649063618,2.796955688762793,85.01499366760254,2.0564961670024786
+3122.4489795918366,1.2406641077706269,0.13181727010191158,2.7923813905663906,85.01675605773926,2.0951724590049707
+3132.6530612244896,1.238642953777756,0.13422248573082982,2.7878294624010636,85.01809120178223,2.0972574170009466
+3142.8571428571427,1.236631645632798,0.13633823580740365,2.7832997225298612,85.0163745880127,2.0873686249979073
+3153.0612244897957,1.2346301036561727,0.13821710815111704,2.7787919912759236,85.01848793029785,2.097862000002351
+3163.265306122449,1.2326382490680174,0.13983846403834502,2.7743060909923543,85.01590156555176,2.0992807500006165
+3173.469387755102,1.2306560039752128,0.14117053200875668,2.769841846033401,84.93197059631348,2.2894407080020756
+3183.673469387755,1.2286832913589905,0.1421582740966005,2.7653990827263613,84.93498420715332,2.2727404170000227
+3193.877551020408,1.2267200350616605,0.14285360880519238,2.7609776293410704,84.93538856506348,2.296773124995525
+3204.081632653061,1.224766159775001,0.1433325882067923,2.756577316063982,84.93608283996582,2.2942639579996467
+3214.285714285714,1.2228215910274258,0.14355222806185072,2.7521979749698744,84.93271827697754,2.272806374996435
+3224.4897959183672,1.2208862551725304,0.1434894852779631,2.7478394399949053,84.93325233459473,2.27232012499735
+3234.6938775510203,1.2189600793773963,0.14310373228161155,2.7435015469102098,84.93231391906738,2.3244632089990773
+3244.8979591836733,1.2170429916107395,0.14244057442198585,2.739184133296135,84.93586921691895,2.2839777499975753
+3255.1020408163267,1.215134920631698,0.1415918213399271,2.734887038517215,84.93631935119629,2.1469258750003064
+3265.3061224489797,1.2132357959792444,0.14050479120613238,2.730610103695639,84.93778419494629,2.14379629099858
+3275.5102040816328,1.2113455479603203,0.1391603402382602,2.7263531716875775,84.93343544006348,2.14694537500327
+3285.714285714286,1.2094641076398034,0.13753459133567358,2.7221160870589216,84.9362735748291,2.143147915994632
+3295.918367346939,1.2075914068296498,0.13566034565307283,2.717898696061596,84.93425941467285,2.1381772919994546
+3306.122448979592,1.2057273780788194,0.13363547415838872,2.7137008466090293,84.9349308013916,2.1345859580032993
+3316.326530612245,1.2038719546625742,0.13141668775132864,2.7095223882545696,84.9357852935791,2.1545390419996693
+3326.530612244898,1.202025070572816,0.1289808802789797,2.705363172167395,84.93439674377441,2.1422923329955665
+3336.734693877551,1.2001866605082938,0.12632108206483475,2.7012230511118815,84.92031288146973,2.1107044170057634
+3346.9387755102043,1.1983566598644586,0.12345664375668551,2.697101879424281,84.91999244689941,2.102077042000019
+3357.142857142857,1.1965350047244243,0.12047708880895439,2.692999512991989,84.9278736114502,2.098464167000202
+3367.3469387755104,1.1947216318492764,0.11737053039076943,2.688915809231972,84.92130470275879,2.143697291998251
+3377.5510204081634,1.192916478668863,0.11410202711788253,2.68485062707056,84.91884803771973,2.1284154579989263
+3387.7551020408164,1.191119483273141,0.11067862501500443,2.6808038269218883,84.92290687561035,2.1247713749980903
+3397.9591836734694,1.1893305844025122,0.10711013674860542,2.6767752706687986,84.92120552062988,2.129636583995307
+3408.1632653061224,1.1875497214397939,0.10346448216096359,2.6727648216425592,84.92266273498535,2.152924542002438
+3418.3673469387754,1.1857768344011674,0.09977735974749373,2.668772344603795,84.92036628723145,2.125126792001538
+3428.5714285714284,1.184011863927779,0.0959957082207547,2.6647977057224637,84.91555976867676,2.1324860000022454
+3438.7755102040815,1.18225475127727,0.09213395099258928,2.6608407725598227,84.91707801818848,2.113811125003849
+3448.9795918367345,1.1805054383160325,0.08819939158128533,2.6569014140504237,84.92106056213379,2.0870988750029937
+3459.183673469388,1.1787638675105825,0.08422678680429234,2.6529795004816066,84.92057991027832,2.0757515000004787
+3469.387755102041,1.1770299819197163,0.08030712724149155,2.649074903478379,84.91529273986816,2.080242374999216
+3479.591836734694,1.1753037251871348,0.07636533296077787,2.645187495983606,84.91929817199707,2.084310042002471
+3489.795918367347,1.1735850415331726,0.07241538518213522,2.641317152242152,84.91849708557129,2.067858874994272
+3500.0,1.171873875747508,0.06847166539588619,2.637463747782448,84.92414283752441,1.9157531250020838
diff --git a/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_memory_comparison_rcwa.png b/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_memory_comparison_rcwa.png
new file mode 100644
index 0000000..afa171e
Binary files /dev/null and b/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_memory_comparison_rcwa.png differ
diff --git a/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_profile.png b/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_profile.png
index 13ddc27..0a6a631 100644
Binary files a/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_profile.png and b/examples/simulation/blazed_multilayer_memory_comparison/results/blazed_multilayer_profile.png differ
diff --git a/examples/simulation/blazed_multilayer_memory_comparison/results/multilayer_stack_schematic.png b/examples/simulation/blazed_multilayer_memory_comparison/results/multilayer_stack_schematic.png
index 8dce6a2..18f1db8 100644
Binary files a/examples/simulation/blazed_multilayer_memory_comparison/results/multilayer_stack_schematic.png and b/examples/simulation/blazed_multilayer_memory_comparison/results/multilayer_stack_schematic.png differ
diff --git a/examples/simulation/blazed_multilayer_sweep/blazed_multilayer_sweep.py b/examples/simulation/blazed_multilayer_sweep/blazed_multilayer_sweep.py
index ff467f7..626b1f3 100644
--- a/examples/simulation/blazed_multilayer_sweep/blazed_multilayer_sweep.py
+++ b/examples/simulation/blazed_multilayer_sweep/blazed_multilayer_sweep.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import argparse
 from pathlib import Path
 
 import numpy as np
@@ -38,32 +39,45 @@
     polarization="p",
 )
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=20,
-    show_progress=True,
-    live_plot=True,
-    live_plot_x_key="energy_ev",
-    backend="numba",
+parser = argparse.ArgumentParser(description="Blazed multilayer energy sweep")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
 )
+args = parser.parse_args()
 
-csv_path = output_dir / "blazed_multilayer_all_orders.csv"
-orders_plot_path = output_dir / "blazed_multilayer_orders_1_3.png"
-profile_plot_path = output_dir / "blazed_multilayer_profile.png"
-stack_plot_path = output_dir / "multilayer_stack_schematic.png"
+if __name__ == "__main__":
+    runner = grax.BatchSimulationRunner(
+        solver=args.solver,
+        diffraction_order=1,
+        fourier_orders=20,
+        show_progress=True,
+        live_plot=True,
+        live_plot_x_key="energy_ev",
+        max_workers="auto",
+        backend="numba",
+    )
 
-results = list(runner.run_cases(cases))
-grax.write_all_orders_csv(results, csv_path)
-grax.plot_order_subset(
-    results,
-    orders_plot_path,
-    diffraction_orders=[1, 2, 3],
-    title="Blazed Multilayer Monochromator Sweep: Orders 1-3",
-)
-grating.plot_profile(profile_plot_path)
-multilayer_stack.plot_schematic(stack_plot_path)
+    csv_path = output_dir / f"blazed_multilayer_all_orders_{args.solver}.csv"
+    orders_plot_path = output_dir / f"blazed_multilayer_orders_1_3_{args.solver}.png"
+    profile_plot_path = output_dir / "blazed_multilayer_profile.png"
+    stack_plot_path = output_dir / "multilayer_stack_schematic.png"
+
+    results = list(runner.run_cases(cases))
+    grax.write_all_orders_csv(results, csv_path)
+    grax.plot_order_subset(
+        results,
+        orders_plot_path,
+        diffraction_orders=[1, 2, 3],
+        title="Blazed Multilayer Monochromator Sweep: Orders 1-3",
+    )
+    grating.plot_profile(profile_plot_path)
+    multilayer_stack.plot_schematic(stack_plot_path)
 
-print(f"Results saved to: {csv_path}")
-print(f"Orders 1-3 plot saved to: {orders_plot_path}")
-print(f"Profile plot saved to: {profile_plot_path}")
-print(f"Stack schematic saved to: {stack_plot_path}")
+    print(f"Results saved to: {csv_path}")
+    print(f"Orders 1-3 plot saved to: {orders_plot_path}")
+    print(f"Profile plot saved to: {profile_plot_path}")
+    print(f"Stack schematic saved to: {stack_plot_path}")
diff --git a/examples/simulation/blazed_multilayer_sweep/polarization_comparison.py b/examples/simulation/blazed_multilayer_sweep/polarization_comparison.py
index 6f653b1..d0b4e61 100644
--- a/examples/simulation/blazed_multilayer_sweep/polarization_comparison.py
+++ b/examples/simulation/blazed_multilayer_sweep/polarization_comparison.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import argparse
 from pathlib import Path
 
 import matplotlib.pyplot as plt
@@ -33,65 +34,79 @@
 energies_ev = np.arange(500.0, 4000.0, 10.0)
 diffraction_orders = [1, 2, 3]
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=20,
-    show_progress=True,
-    live_plot=False,
-    backend="numba",
+parser = argparse.ArgumentParser(description="Polarization comparison (s vs p)")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
 )
+args = parser.parse_args()
 
-results_s = list(runner.run_cases(
-    grax.monochromator_cases(
-        grating=grating,
-        energies_ev=energies_ev,
+if __name__ == "__main__":
+    runner = grax.BatchSimulationRunner(
+        solver=args.solver,
         diffraction_order=1,
-        cff=2.25,
-        polarization="s",
+        fourier_orders=20,
+        show_progress=True,
+        live_plot=True,
+        live_plot_x_key="energy_ev",
+        max_workers="auto",
+        backend="numba",
     )
-))
-results_p = list(runner.run_cases(
-    grax.monochromator_cases(
-        grating=grating,
-        energies_ev=energies_ev,
-        diffraction_order=1,
-        cff=2.25,
-        polarization="p",
-    )
-))
-
-
-def sorted_ok(results):
-    return sorted([r for r in results if r.status == "ok"], key=lambda r: float(r.energy_ev))
-
 
-collected_s = sorted_ok(results_s)
-collected_p = sorted_ok(results_p)
-energies = np.asarray([r.energy_ev for r in collected_s], dtype=float)
-
-comparison_plot_path = output_dir / "blazed_multilayer_pol_comparison.png"
-colors = ["tab:blue", "tab:orange", "tab:green"]
-
-figure, axis = plt.subplots(figsize=(10, 6))
-for index, order in enumerate(diffraction_orders):
-    eff_s = np.asarray(
-        [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in collected_s],
-        dtype=float,
-    )
-    eff_p = np.asarray(
-        [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in collected_p],
-        dtype=float,
-    )
-    axis.plot(energies, eff_s, "-", color=colors[index], linewidth=1.5, markersize=2, label=f"Order {order} (s)")
-    axis.plot(energies, eff_p, "--", color=colors[index], linewidth=1.5, markersize=2, label=f"Order {order} (p)")
-
-axis.set_xlabel("Photon Energy (eV)")
-axis.set_ylabel("Diffraction Efficiency")
-axis.set_title("Blazed Multilayer Sweep: s vs p Polarization, Orders 1–3")
-axis.grid(True, alpha=0.3)
-axis.legend(loc="best")
-figure.tight_layout()
-figure.savefig(comparison_plot_path, dpi=150, bbox_inches="tight")
-plt.close(figure)
-
-print(f"Polarization comparison plot saved to: {comparison_plot_path}")
+    results_s = list(runner.run_cases(
+        grax.monochromator_cases(
+            grating=grating,
+            energies_ev=energies_ev,
+            diffraction_order=1,
+            cff=2.25,
+            polarization="s",
+        )
+    ))
+    results_p = list(runner.run_cases(
+        grax.monochromator_cases(
+            grating=grating,
+            energies_ev=energies_ev,
+            diffraction_order=1,
+            cff=2.25,
+            polarization="p",
+        )
+    ))
+
+
+    def sorted_ok(results):
+        return sorted([r for r in results if r.status == "ok"], key=lambda r: float(r.energy_ev))
+
+
+    collected_s = sorted_ok(results_s)
+    collected_p = sorted_ok(results_p)
+    energies = np.asarray([r.energy_ev for r in collected_s], dtype=float)
+
+    comparison_plot_path = output_dir / f"blazed_multilayer_pol_comparison_{args.solver}.png"
+    colors = ["tab:blue", "tab:orange", "tab:green"]
+
+    figure, axis = plt.subplots(figsize=(10, 6))
+    for index, order in enumerate(diffraction_orders):
+        eff_s = np.asarray(
+            [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in collected_s],
+            dtype=float,
+        )
+        eff_p = np.asarray(
+            [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in collected_p],
+            dtype=float,
+        )
+        axis.plot(energies, eff_s, "-", color=colors[index], linewidth=1.5, markersize=2, label=f"Order {order} (s)")
+        axis.plot(energies, eff_p, "--", color=colors[index], linewidth=1.5, markersize=2, label=f"Order {order} (p)")
+
+    axis.set_xlabel("Photon Energy (eV)")
+    axis.set_ylabel("Diffraction Efficiency")
+    axis.set_title("Blazed Multilayer Sweep: s vs p Polarization, Orders 1–3")
+    axis.grid(True, alpha=0.3)
+    axis.legend(loc="best")
+    figure.tight_layout()
+    figure.savefig(comparison_plot_path, dpi=150, bbox_inches="tight")
+    plt.close(figure)
+
+    print(f"Polarization comparison plot saved to: {comparison_plot_path}")
diff --git a/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_all_orders.csv b/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_all_orders.csv
deleted file mode 100644
index 300f68c..0000000
--- a/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_all_orders.csv
+++ /dev/null
@@ -1,3851 +0,0 @@
-case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
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-blazed-multilayer-00000140,1900.0,1.5901845425947414,-5,7.714779037820826e-07,7.349378438221791
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-blazed-multilayer-00000141,1910.0,1.5860200818353718,-5,8.879680957370776e-07,7.3300885059011875
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-blazed-multilayer-00000142,1920.0,1.5818881689370983,-5,7.308491400180788e-07,7.310949671805247
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-blazed-multilayer-00000143,1930.0,1.5777883821278351,-5,5.947194128545055e-07,7.2919599735866
-blazed-multilayer-00000143,1930.0,1.5777883821278351,-4,3.813738481332517e-05,6.559388825578537
-blazed-multilayer-00000143,1930.0,1.5777883821278351,-3,0.00028060585648500674,5.7344321923931005
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-blazed-multilayer-00000144,1940.0,1.5737203072477541,-5,9.455215028689737e-07,7.273117484393083
-blazed-multilayer-00000144,1940.0,1.5737203072477541,-4,4.12012228486041e-05,6.542443841761724
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-blazed-multilayer-00000145,1950.0,1.5696835375736384,-5,1.3329054491495154e-06,7.254420312046676
-blazed-multilayer-00000145,1950.0,1.5696835375736384,-4,3.8844492355580666e-05,6.525629506019925
-blazed-multilayer-00000145,1950.0,1.5696835375736384,-3,0.00025636385881455486,5.7049267425284995
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-blazed-multilayer-00000146,1960.0,1.56567767364794,-5,1.1099112302060897e-06,7.235866598245281
-blazed-multilayer-00000146,1960.0,1.56567767364794,-4,3.3731051822778896e-05,6.508944148078527
-blazed-multilayer-00000146,1960.0,1.56567767364794,-3,0.0002541310025372011,5.690343790162174
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-blazed-multilayer-00000147,1970.0,1.561702323113039,-5,9.510832656636632e-07,7.217454517787104
-blazed-multilayer-00000147,1970.0,1.561702323113039,-4,3.419805562831637e-05,6.492386127406007
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-blazed-multilayer-00000147,1970.0,1.561702323113039,5,0.0,0.0
-blazed-multilayer-00000148,1980.0,1.557757100549395,-5,1.5759820160659032e-06,7.199182277816064
-blazed-multilayer-00000148,1980.0,1.557757100549395,-4,3.806490533891706e-05,6.475953832536291
-blazed-multilayer-00000148,1980.0,1.557757100549395,-3,0.00022401747817613952,5.661510264771195
-blazed-multilayer-00000148,1980.0,1.557757100549395,-2,0.02089751320198345,4.708755758673419
-blazed-multilayer-00000148,1980.0,1.557757100549395,-1,0.006041422164820873,3.50671056941205
-blazed-multilayer-00000148,1980.0,1.557757100549395,0,0.019726943319463366,1.5577571005496083
-blazed-multilayer-00000148,1980.0,1.557757100549395,1,0.0,0.0
-blazed-multilayer-00000148,1980.0,1.557757100549395,2,0.0,0.0
-blazed-multilayer-00000148,1980.0,1.557757100549395,3,0.0,0.0
-blazed-multilayer-00000148,1980.0,1.557757100549395,4,0.0,0.0
-blazed-multilayer-00000148,1980.0,1.557757100549395,5,0.0,0.0
-blazed-multilayer-00000149,1990.0,1.553841627318846,-5,1.974623794793842e-06,7.1810481170887925
-blazed-multilayer-00000149,1990.0,1.553841627318846,-4,3.66585452896589e-05,6.459645680410176
-blazed-multilayer-00000149,1990.0,1.553841627318846,-3,0.00020440681513994802,5.6472569012394445
-blazed-multilayer-00000149,1990.0,1.553841627318846,-2,0.02154313313959168,4.696904378536573
-blazed-multilayer-00000149,1990.0,1.553841627318846,-1,0.006203679077603401,3.49788752392854
-blazed-multilayer-00000149,1990.0,1.553841627318846,0,0.01923721711837817,1.553841627318576
-blazed-multilayer-00000149,1990.0,1.553841627318846,1,0.0,0.0
-blazed-multilayer-00000149,1990.0,1.553841627318846,2,0.0,0.0
-blazed-multilayer-00000149,1990.0,1.553841627318846,3,0.0,0.0
-blazed-multilayer-00000149,1990.0,1.553841627318846,4,0.0,0.0
-blazed-multilayer-00000149,1990.0,1.553841627318846,5,0.0,0.0
-blazed-multilayer-00000150,2000.0,1.5499555314121665,-5,1.440734222974272e-06,7.163050305261734
-blazed-multilayer-00000150,2000.0,1.5499555314121665,-4,2.8329223129067444e-05,6.443460115734936
-blazed-multilayer-00000150,2000.0,1.5499555314121665,-3,0.0001970264506433723,5.63311065093221
-blazed-multilayer-00000150,2000.0,1.5499555314121665,-2,0.02296008938217938,4.6851420358783
-blazed-multilayer-00000150,2000.0,1.5499555314121665,-1,0.006228751583985139,3.489130742637286
-blazed-multilayer-00000150,2000.0,1.5499555314121665,0,0.01876166033202043,1.5499555314121096
-blazed-multilayer-00000150,2000.0,1.5499555314121665,1,0.0,0.0
-blazed-multilayer-00000150,2000.0,1.5499555314121665,2,0.0,0.0
-blazed-multilayer-00000150,2000.0,1.5499555314121665,3,0.0,0.0
-blazed-multilayer-00000150,2000.0,1.5499555314121665,4,0.0,0.0
-blazed-multilayer-00000150,2000.0,1.5499555314121665,5,0.0,0.0
-blazed-multilayer-00000151,2010.0,1.5460984473000394,-5,1.539105479733076e-06,7.145187142197031
-blazed-multilayer-00000151,2010.0,1.5460984473000394,-4,1.9778423801064825e-05,6.427395610360591
-blazed-multilayer-00000151,2010.0,1.5460984473000394,-3,0.00019334254780313328,5.619070178951972
-blazed-multilayer-00000151,2010.0,1.5460984473000394,-2,0.02680229816735493,4.673467621379672
-blazed-multilayer-00000151,2010.0,1.5460984473000394,-1,0.005997802665875643,3.4804394002232897
-blazed-multilayer-00000151,2010.0,1.5460984473000394,0,0.018292989602301173,1.5460984473001105
-blazed-multilayer-00000151,2010.0,1.5460984473000394,1,0.0,0.0
-blazed-multilayer-00000151,2010.0,1.5460984473000394,2,0.0,0.0
-blazed-multilayer-00000151,2010.0,1.5460984473000394,3,0.0,0.0
-blazed-multilayer-00000151,2010.0,1.5460984473000394,4,0.0,0.0
-blazed-multilayer-00000151,2010.0,1.5460984473000394,5,0.0,0.0
-blazed-multilayer-00000152,2020.0,1.5422700157892422,-5,3.136606903264213e-06,7.127456957288587
-blazed-multilayer-00000152,2020.0,1.5422700157892422,-4,1.7145600793161757e-05,6.41145066267471
-blazed-multilayer-00000152,2020.0,1.5422700157892422,-3,0.00017941388068567224,5.605134173576502
-blazed-multilayer-00000152,2020.0,1.5422700157892422,-2,0.03172960324574226,4.661880044975575
-blazed-multilayer-00000152,2020.0,1.5422700157892422,-1,0.005690443893776643,3.471812685691887
-blazed-multilayer-00000152,2020.0,1.5422700157892422,0,0.017829371382680294,1.5422700157893559
-blazed-multilayer-00000152,2020.0,1.5422700157892422,1,0.0,0.0
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diff --git a/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_all_orders_rcwa.csv b/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_all_orders_rcwa.csv
new file mode 100644
index 0000000..70d9ae5
--- /dev/null
+++ b/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_all_orders_rcwa.csv
@@ -0,0 +1,14351 @@
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diff --git a/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_orders_1_3.png b/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_orders_1_3.png
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diff --git a/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_pol_comparison_rcwa.png b/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_pol_comparison_rcwa.png
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diff --git a/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_profile.png b/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_profile.png
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diff --git a/examples/simulation/blazed_multilayer_sweep/results/multilayer_stack_schematic.png b/examples/simulation/blazed_multilayer_sweep/results/multilayer_stack_schematic.png
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diff --git a/examples/simulation/continuous_vs_staircase/continuous_vs_staircase.py b/examples/simulation/continuous_vs_staircase/continuous_vs_staircase.py
new file mode 100644
index 0000000..bc2e431
--- /dev/null
+++ b/examples/simulation/continuous_vs_staircase/continuous_vs_staircase.py
@@ -0,0 +1,189 @@
+"""Why the differential method does not need a fine z grid.
+
+Both solvers normally see the same geometry: a grating profile is sliced into
+z-layers of ``z_resolution_nm``, each layer treated as z-invariant. That
+staircase is an approximation of the real profile, and its error shrinks as the
+slices get thinner, which is why a converged run needs a fine z grid and pays
+for it in runtime.
+
+``NeviereOptions(z_sampling="continuous")`` drops the staircase entirely. The
+differential method re-expands the permittivity from the true profile as it
+integrates, so its answer does not depend on ``z_resolution_nm`` at all.
+
+This example sweeps ``z_resolution_nm`` over a sinusoidal profile and plots
+three curves:
+
+- RCWA, staircase: converges as z refines
+- Nevière with ``z_sampling="textures"``: the same staircase, so it converges
+  identically -- this is what makes the two solvers comparable elsewhere
+- Nevière with ``z_sampling="continuous"``: flat, because it never sees a
+  staircase to converge from
+
+The flat line is the converged answer. The distance from a staircase curve to it
+is the discretization error a staircase run is carrying at that resolution.
+"""
+
+from __future__ import annotations
+
+import argparse
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+import grax
+
+parser = argparse.ArgumentParser(description="Staircase vs continuous z sampling")
+parser.add_argument(
+    "--polarization",
+    choices=("s", "p"),
+    default="p",
+    help="Incident polarization.",
+)
+args = parser.parse_args()
+
+output_dir = Path(__file__).resolve().parent / "results"
+output_dir.mkdir(parents=True, exist_ok=True)
+
+PERIOD_LPERMM = 800
+DEPTH_NM = 12.0
+ENERGY_EV = 300.0
+GRAZING_ANGLE_DEG = 5.0
+FOURIER_ORDERS = 10
+DIFFRACTION_ORDER = 1
+
+period_nm = 1e6 / PERIOD_LPERMM
+x_points_nm = np.linspace(0.0, period_nm, 129)
+z_points_nm = DEPTH_NM * 0.5 * (1.0 - np.cos(2.0 * np.pi * x_points_nm / period_nm))
+
+
+def build_grating(z_resolution_nm: float) -> grax.ProfileGrating:
+    """Return the sinusoidal grating sliced at one z resolution.
+
+    Args:
+        z_resolution_nm: Vertical slice thickness in nanometers.
+
+    Returns:
+        Configured sinusoidal profile grating.
+    """
+
+    return grax.ProfileGrating(
+        period_lpermm=PERIOD_LPERMM,
+        x_points_nm=x_points_nm,
+        z_points_nm=z_points_nm,
+        substrate_material="Si",
+        layer_material="Au",
+        layer_thickness_nm=20.0,
+        x_resolution_nm=1.0,
+        z_resolution_nm=z_resolution_nm,
+    )
+
+
+def efficiency(z_resolution_nm: float, solver: str, solver_options=None) -> float:
+    """Return the selected-order efficiency for one configuration.
+
+    Args:
+        z_resolution_nm: Vertical slice thickness in nanometers.
+        solver: ``"rcwa"`` or ``"neviere"``.
+        solver_options: Optional solver settings.
+
+    Returns:
+        Efficiency of the selected reflected order.
+    """
+
+    result = grax.run_simulation(
+        grating=build_grating(z_resolution_nm),
+        energy_ev=ENERGY_EV,
+        grazing_angle_deg=GRAZING_ANGLE_DEG,
+        diffraction_order=DIFFRACTION_ORDER,
+        fourier_orders=FOURIER_ORDERS,
+        polarization=args.polarization,
+        solver=solver,
+        solver_options=solver_options,
+        validate_physical_results=False,
+    )
+    return float(result.selected_efficiency)
+
+
+z_resolutions_nm = np.asarray([2.0, 1.0, 0.5, 0.25, 0.1, 0.05], dtype=float)
+continuous_options = grax.NeviereOptions(z_sampling="continuous", sample_phase=0.005)
+
+curves = {
+    "RCWA (staircase)": [efficiency(z, "rcwa") for z in z_resolutions_nm],
+    "Nevière (staircase)": [efficiency(z, "neviere") for z in z_resolutions_nm],
+    "Nevière (continuous)": [
+        efficiency(z, "neviere", continuous_options) for z in z_resolutions_nm
+    ],
+}
+curves = {label: np.asarray(values, dtype=float) for label, values in curves.items()}
+
+converged = curves["Nevière (continuous)"].mean()
+continuous_spread = float(np.ptp(curves["Nevière (continuous)"]))
+
+figure, axes = plt.subplots(2, 1, figsize=(10, 8), sharex=True)
+value_axis, error_axis = axes
+
+styles = {
+    "RCWA (staircase)": {"linestyle": "-", "marker": "o"},
+    "Nevière (staircase)": {"linestyle": (0, (6, 4)), "marker": "s"},
+    "Nevière (continuous)": {"linestyle": "-.", "marker": "^"},
+}
+for label, values in curves.items():
+    value_axis.plot(z_resolutions_nm, values, linewidth=1.6, markersize=5,
+                    label=label, **styles[label])
+value_axis.set_xscale("log")
+value_axis.set_ylabel(f"Order {DIFFRACTION_ORDER} efficiency")
+value_axis.set_title(
+    f"Sinusoidal grating at {ENERGY_EV:.0f} eV, {args.polarization} polarization: "
+    "staircase convergence vs continuous sampling"
+)
+value_axis.grid(True, alpha=0.3)
+value_axis.legend(loc="best")
+
+staircase_errors = np.concatenate([
+    np.abs(curves[label] - converged)
+    for label in ("RCWA (staircase)", "Nevière (staircase)")
+])
+error_floor = staircase_errors[staircase_errors > 0].min() / 50.0
+for label, values in curves.items():
+    error = np.abs(values - converged)
+    if label == "Nevière (continuous)":
+        # Exactly zero at every resolution, which a log axis cannot draw. Pin it
+        # to a floor and label it honestly rather than letting it vanish.
+        error = np.full_like(error, error_floor)
+        label = f"{label} - exactly 0, shown at the axis floor"
+    error_axis.plot(z_resolutions_nm, error, linewidth=1.4, markersize=5,
+                    label=label, **styles[label.split(" - ")[0]])
+error_axis.set_xscale("log")
+error_axis.set_yscale("log")
+error_axis.set_ylim(error_floor / 3.0, staircase_errors.max() * 3.0)
+error_axis.invert_xaxis()
+error_axis.set_xlabel("z_resolution_nm  (finer to the right)")
+error_axis.set_ylabel("|efficiency - converged|")
+error_axis.grid(True, alpha=0.3, which="both")
+error_axis.legend(loc="best", fontsize=8)
+
+figure.tight_layout()
+plot_path = output_dir / f"continuous_vs_staircase_{args.polarization}.png"
+figure.savefig(plot_path, dpi=150, bbox_inches="tight")
+plt.close(figure)
+
+csv_path = output_dir / f"continuous_vs_staircase_{args.polarization}.csv"
+np.savetxt(
+    csv_path,
+    np.column_stack([z_resolutions_nm, *curves.values()]),
+    delimiter=",",
+    header="z_resolution_nm,rcwa_staircase,neviere_staircase,neviere_continuous",
+    comments="",
+)
+
+print(f"Swept z_resolution_nm from {z_resolutions_nm.max()} down to {z_resolutions_nm.min()} nm.")
+print(f"  continuous sampling spread over the whole sweep : {continuous_spread:.3e}")
+print(f"  coarsest staircase error (z = {z_resolutions_nm.max()} nm)          : "
+      f"{abs(curves['RCWA (staircase)'][0] - converged):.3e}")
+print(f"  finest staircase error   (z = {z_resolutions_nm.min()} nm)         : "
+      f"{abs(curves['RCWA (staircase)'][-1] - converged):.3e}")
+print("  the two staircase curves agree with each other to "
+      f"{np.max(np.abs(curves['RCWA (staircase)'] - curves['Nevière (staircase)'])):.3e}")
+print(f"Plot saved to: {plot_path}")
+print(f"CSV saved to: {csv_path}")
diff --git a/examples/simulation/continuous_vs_staircase/results/continuous_vs_staircase_p.csv b/examples/simulation/continuous_vs_staircase/results/continuous_vs_staircase_p.csv
new file mode 100644
index 0000000..cb3f067
--- /dev/null
+++ b/examples/simulation/continuous_vs_staircase/results/continuous_vs_staircase_p.csv
@@ -0,0 +1,7 @@
+z_resolution_nm,rcwa_staircase,neviere_staircase,neviere_continuous
+2.000000000000000000e+00,7.918595136399533829e-02,7.918595136460478134e-02,8.189920658716579038e-02
+1.000000000000000000e+00,8.202473757066647275e-02,8.202473757088624140e-02,8.189920658716579038e-02
+5.000000000000000000e-01,8.201060384585046048e-02,8.201060384620474653e-02,8.189920658716579038e-02
+2.500000000000000000e-01,8.195044141743743071e-02,8.195044141783855429e-02,8.189920658716579038e-02
+1.000000000000000056e-01,8.191273910748245179e-02,8.191273910806842751e-02,8.189920658716579038e-02
+5.000000000000000278e-02,8.191171616801480593e-02,8.191171616822133517e-02,8.189920658716579038e-02
diff --git a/examples/simulation/continuous_vs_staircase/results/continuous_vs_staircase_p.png b/examples/simulation/continuous_vs_staircase/results/continuous_vs_staircase_p.png
new file mode 100644
index 0000000..53b7ee9
Binary files /dev/null and b/examples/simulation/continuous_vs_staircase/results/continuous_vs_staircase_p.png differ
diff --git a/examples/simulation/deep_grating_limits/deep_grating_limits.py b/examples/simulation/deep_grating_limits/deep_grating_limits.py
new file mode 100644
index 0000000..99886af
--- /dev/null
+++ b/examples/simulation/deep_grating_limits/deep_grating_limits.py
@@ -0,0 +1,215 @@
+"""Where the modal solver runs out of range and the differential method does not.
+
+The two solvers normally agree to ~1e-11, so most comparisons between them are
+uninteresting. This is the case where they genuinely differ.
+
+The modal (RCWA) solver treats each layer as z-invariant and evaluates
+``q / sinh(q d)`` across the whole layer at once. For a deep, high-contrast
+grating the evanescent orders make ``q d`` large, ``sinh`` overflows to infinity,
+and the solve raises "Modal layer function produced NaN/Inf values".
+
+The differential method never forms that quantity. It caps the optical thickness
+of any transfer matrix it builds (``NeviereOptions.block_phase``) and combines
+the pieces with an interface-response cascade, which is an R-matrix propagation
+and cannot accumulate a growing exponential.
+
+Geometry is the published RETICOLO ``exemple1_1D`` lamellar grating: wavelength
+6 um, period 10 um, refractive index 1.5 ridges over vacuum grooves, at normal
+incidence. Groove depth is swept from a fraction of a wavelength to well past
+the point where the modal solver gives up.
+
+The transmission oscillates with depth because a deep grating acts as a
+Fabry-Perot cavity. The depths are log-spaced, so those fringes are deliberately
+undersampled at the deep end: the jaggedness there is aliasing of real
+interference, not solver noise. The energy balance in the lower panel is the
+check that the deep points are trustworthy.
+"""
+
+from __future__ import annotations
+
+import argparse
+import warnings
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+from grax.solvers import res0, res1, res2, res2_dm
+from grax.solvers.common import prepare_layer_stack, propagating_energy_balance
+
+parser = argparse.ArgumentParser(
+    description="Compare solver depth limits on a deep lamellar grating"
+)
+parser.add_argument(
+    "--polarization",
+    choices=("s", "p"),
+    default="p",
+    help="Incident polarization. TM (p) is the harder case for the factorization rules.",
+)
+args = parser.parse_args()
+
+output_dir = Path(__file__).resolve().parent / "results"
+output_dir.mkdir(parents=True, exist_ok=True)
+
+WAVELENGTH_NM = 6000.0
+PERIOD_NM = 10000.0
+FOURIER_ORDERS = 25
+# n = 1.5 ridges over [0, 1] and [9, 10] um, vacuum grooves between.
+GRATING_TEXTURE = [
+    np.array([1000.0, 9000.0]),
+    np.array([1.5, 1.0], dtype=complex),
+]
+STACK = [1.0, 1.5, GRATING_TEXTURE]
+
+depths_nm = np.geomspace(2.0e3, 1.0e6, 28)
+
+
+def solve(depth_nm: float, solver: str) -> tuple[float, float]:
+    """Return zeroth-order transmission and total propagating energy at one depth.
+
+    Args:
+        depth_nm: Groove depth in nanometers.
+        solver: ``"rcwa"`` or ``"neviere"``.
+
+    Returns:
+        Zeroth-order transmission and the summed propagating efficiency, both
+        ``nan`` when the solver cannot reach this depth.
+    """
+
+    parm = res0(1 if args.polarization == "s" else -1)
+    aa = res1(
+        WAVELENGTH_NM,
+        PERIOD_NM,
+        STACK,
+        FOURIER_ORDERS,
+        0.0,
+        parm,
+        _fourier_backend="numba",
+    )
+    profile = ([0.0, float(depth_nm), 0.0], [0, 2, 1])
+    try:
+        # The overflow that ends the modal solver's range is the subject of this
+        # example, not a fault to report, so silence the numpy warning it emits
+        # on the way to raising.
+        with warnings.catch_warnings(), np.errstate(over="ignore", invalid="ignore"):
+            warnings.simplefilter("ignore", RuntimeWarning)
+            result = res2(aa, profile, parm) if solver == "rcwa" else res2_dm(aa, profile, parm)
+    except ValueError:
+        # The modal solver raises once sinh(q d) overflows. That is the point of
+        # this example, so record it rather than aborting the sweep.
+        return float("nan"), float("nan")
+
+    zeroth = int(np.where(result.inc_top_reflected.order == 0)[0][0])
+    n_top, n_bottom, _ = prepare_layer_stack(aa, profile)
+    balance = propagating_energy_balance(
+        result.inc_top_reflected,
+        result.inc_top_transmitted,
+        wavelength=aa.wavelength,
+        period=aa.period,
+        beta0=aa.beta0,
+        n_top=n_top,
+        n_bottom=n_bottom,
+    )
+    return float(result.inc_top_transmitted.efficiency[zeroth]), float(balance["total"])
+
+
+transmission = {solver: [] for solver in ("rcwa", "neviere")}
+energy_balance = {solver: [] for solver in ("rcwa", "neviere")}
+for depth_nm in depths_nm:
+    for solver in ("rcwa", "neviere"):
+        zeroth, total = solve(float(depth_nm), solver)
+        transmission[solver].append(zeroth)
+        energy_balance[solver].append(total)
+
+for solver in ("rcwa", "neviere"):
+    transmission[solver] = np.asarray(transmission[solver], dtype=float)
+    energy_balance[solver] = np.asarray(energy_balance[solver], dtype=float)
+
+depths_in_wavelengths = depths_nm / WAVELENGTH_NM
+rcwa_ok = np.isfinite(transmission["rcwa"])
+last_rcwa_depth = depths_in_wavelengths[rcwa_ok].max() if rcwa_ok.any() else float("nan")
+deepest = depths_in_wavelengths.max()
+
+figure, axes = plt.subplots(2, 1, figsize=(10, 8), sharex=True)
+efficiency_axis, balance_axis = axes
+
+for solver, style in (("rcwa", "-"), ("neviere", "--")):
+    efficiency_axis.plot(
+        depths_in_wavelengths,
+        transmission[solver],
+        style,
+        linewidth=1.6,
+        marker="o",
+        markersize=3,
+        label=f"{solver} zeroth-order transmission",
+    )
+efficiency_axis.axvline(last_rcwa_depth, color="0.4", linestyle=":", linewidth=1.2)
+efficiency_axis.annotate(
+    f"modal solver stops here\n({last_rcwa_depth:.1f} wavelengths)",
+    xy=(last_rcwa_depth, 0.44),
+    xytext=(last_rcwa_depth * 1.6, 0.30),
+    fontsize=9,
+    arrowprops={"arrowstyle": "->", "color": "0.4"},
+)
+efficiency_axis.set_xscale("log")
+efficiency_axis.set_ylabel("Zeroth-order transmission")
+efficiency_axis.set_title(
+    f"Deep lamellar grating, {args.polarization} polarization: solver depth limits"
+)
+efficiency_axis.grid(True, alpha=0.3)
+efficiency_axis.legend(loc="lower left", fontsize=9)
+
+for solver, style in (("rcwa", "-"), ("neviere", "--")):
+    balance_axis.plot(
+        depths_in_wavelengths,
+        np.abs(1.0 - energy_balance[solver]),
+        style,
+        linewidth=1.4,
+        marker="o",
+        markersize=3,
+        label=f"{solver}",
+    )
+balance_axis.set_yscale("log")
+balance_axis.set_xscale("log")
+balance_axis.set_xlabel("Groove depth (wavelengths)")
+balance_axis.set_ylabel("|1 - energy balance|")
+balance_axis.grid(True, alpha=0.3, which="both")
+balance_axis.legend(loc="best")
+
+figure.tight_layout()
+plot_path = output_dir / f"deep_grating_limits_{args.polarization}.png"
+figure.savefig(plot_path, dpi=150, bbox_inches="tight")
+plt.close(figure)
+
+csv_path = output_dir / f"deep_grating_limits_{args.polarization}.csv"
+np.savetxt(
+    csv_path,
+    np.column_stack(
+        [
+            depths_nm,
+            depths_in_wavelengths,
+            transmission["rcwa"],
+            transmission["neviere"],
+            energy_balance["rcwa"],
+            energy_balance["neviere"],
+        ]
+    ),
+    delimiter=",",
+    header="depth_nm,depth_wavelengths,t0_rcwa,t0_neviere,energy_rcwa,energy_neviere",
+    comments="",
+)
+
+matched = rcwa_ok & np.isfinite(transmission["neviere"])
+print(f"Swept {len(depths_nm)} depths from "
+      f"{depths_in_wavelengths.min():.2f} to {deepest:.0f} wavelengths.")
+print(f"  modal solver succeeded up to     : {last_rcwa_depth:.1f} wavelengths "
+      f"({int(rcwa_ok.sum())}/{len(depths_nm)} depths)")
+print(f"  differential method succeeded up to: {deepest:.0f} wavelengths "
+      f"({int(np.isfinite(transmission['neviere']).sum())}/{len(depths_nm)} depths)")
+if matched.any():
+    deviation = np.abs(transmission["rcwa"][matched] - transmission["neviere"][matched]).max()
+    print(f"  where both work, max |dT0|       : {deviation:.3e}")
+worst_balance = np.nanmax(np.abs(1.0 - energy_balance["neviere"]))
+print(f"  differential-method energy balance stays within {worst_balance:.1e} of 1")
+print(f"Plot saved to: {plot_path}")
+print(f"CSV saved to: {csv_path}")
diff --git a/examples/simulation/deep_grating_limits/results/deep_grating_limits_p.csv b/examples/simulation/deep_grating_limits/results/deep_grating_limits_p.csv
new file mode 100644
index 0000000..f1673e3
--- /dev/null
+++ b/examples/simulation/deep_grating_limits/results/deep_grating_limits_p.csv
@@ -0,0 +1,29 @@
+depth_nm,depth_wavelengths,t0_rcwa,t0_neviere,energy_rcwa,energy_neviere
+2.000000000000000000e+03,3.333333333333333148e-01,8.959105593806218071e-01,8.959105593804578271e-01,9.999999999999995559e-01,9.999999999998012701e-01
+2.517629667834576594e+03,4.196049446390960891e-01,8.603083386187743153e-01,8.603083386185220727e-01,9.999999999999945599e-01,9.999999999997073452e-01
+3.169229572180423020e+03,5.282049286967371859e-01,8.221172521916431108e-01,8.221172521914106301e-01,1.000000000000001332e+00,9.999999999997059019e-01
+3.989473197550057193e+03,6.649121995916762451e-01,7.438965666348940076e-01,7.438965666347960859e-01,1.000000000000002887e+00,9.999999999998669953e-01
+5.022008040591447752e+03,8.370013400985746310e-01,6.128892113888161353e-01,6.128892113894355287e-01,1.000000000000004219e+00,1.000000000000672351e+00
+6.321778217548408065e+03,1.053629702924734568e+00,4.874062965565698624e-01,4.874062965569977424e-01,1.000000000000003775e+00,1.000000000000480282e+00
+7.957948196985137656e+03,1.326324699497522852e+00,3.062958277304456689e-01,3.062958277301762733e-01,1.000000000000006439e+00,9.999999999995695665e-01
+1.001758323791022849e+04,1.669597206318371496e+00,1.860114943628486395e-01,1.860114943625410522e-01,1.000000000000012879e+00,9.999999999993622879e-01
+1.261028237988257206e+04,2.101713729980428713e+00,2.152995787869416422e-01,2.152995787867683086e-01,1.000000000000007327e+00,9.999999999998675504e-01
+1.587401051968198590e+04,2.645668419946997751e+00,5.061523845790353304e-01,5.061523845787356812e-01,1.000000000000004441e+00,9.999999999998868683e-01
+1.998243991593476312e+04,3.330406652655793831e+00,9.105846698224403513e-01,9.105846698228320379e-01,1.000000000000004441e+00,1.000000000000530243e+00
+2.515419178403965634e+04,4.192365297339942565e+00,7.819029147386256096e-01,7.819029147377982714e-01,1.000000000000003775e+00,9.999999999988297139e-01
+3.166446975294949516e+04,5.277411625491582825e+00,1.918673688041099279e-01,1.918673688046675374e-01,1.000000000000008216e+00,1.000000000002087663e+00
+3.985970423313810898e+04,6.643284038856351437e+00,7.734665950310102289e-01,7.734665950276943258e-01,1.000000000000001332e+00,9.999999999965074604e-01
+5.017598696422997455e+04,8.362664494038329011e+00,4.350665527600451332e-01,4.350665527615389938e-01,1.000000000000008660e+00,1.000000000002438938e+00
+6.316227669701317063e+04,1.052704611616886154e+01,nan,8.991662097561659017e-01,nan,1.000000000002130518e+00
+7.950961085018843005e+04,1.325160180836473778e+01,nan,3.457462563398255306e-01,nan,1.000000000008111956e+00
+1.000878775772081572e+05,1.668131292953469114e+01,nan,2.553800196832031744e-01,nan,9.999999999993676170e-01
+1.259921049894871539e+05,2.099868416491452550e+01,nan,6.852889497186667178e-01,nan,9.999999999922155602e-01
+1.586007307172311121e+05,2.643345511953851812e+01,nan,4.484001155373419367e-01,nan,9.999999999922913885e-01
+1.996489524969718186e+05,3.327482541616196698e+01,nan,7.250661359846951592e-01,nan,9.999999999905915260e-01
+2.513210629792361287e+05,4.188684382987268862e+01,nan,2.103466631452702296e-01,nan,1.000000000013754331e+00
+3.163666821541234385e+05,5.272778035902057070e+01,nan,1.998098915709596857e-01,nan,1.000000000012351453e+00
+3.982470724528063438e+05,6.637451207546772025e+01,nan,3.691058621684191743e-01,nan,1.000000000015794477e+00
+5.013193223677266506e+05,8.355322039462110695e+01,nan,9.267277711371143534e-01,nan,1.000000000026493696e+00
+6.310681995258572279e+05,1.051780332543095398e+02,nan,9.488179839152557360e-01,nan,1.000000000004311440e+00
+7.943980107766239671e+05,1.323996684627706486e+02,nan,2.117932246831843446e-01,nan,9.999999999600125422e-01
+1.000000000000000000e+06,1.666666666666666572e+02,nan,9.482703972843795626e-01,nan,1.000000000009157564e+00
diff --git a/examples/simulation/deep_grating_limits/results/deep_grating_limits_p.png b/examples/simulation/deep_grating_limits/results/deep_grating_limits_p.png
new file mode 100644
index 0000000..916c697
Binary files /dev/null and b/examples/simulation/deep_grating_limits/results/deep_grating_limits_p.png differ
diff --git a/examples/simulation/energy_angle_sweep/energy_angle_sweep.py b/examples/simulation/energy_angle_sweep/energy_angle_sweep.py
index 5f20c7f..79661a1 100644
--- a/examples/simulation/energy_angle_sweep/energy_angle_sweep.py
+++ b/examples/simulation/energy_angle_sweep/energy_angle_sweep.py
@@ -6,6 +6,7 @@
 
 from __future__ import annotations
 
+import argparse
 from pathlib import Path
 
 import matplotlib.pyplot as plt
@@ -55,42 +56,56 @@
     polarization="p",
 )
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=2,
-    default_fourier_orders=5,
-    show_progress=True,
-    live_plot=False,
-    on_error="fail_fast",
-    backend="numba",
+parser = argparse.ArgumentParser(description="Energy-angle pair sweep")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
 )
+args = parser.parse_args()
+
+if __name__ == "__main__":
+    runner = grax.BatchSimulationRunner(
+        solver=args.solver,
+        diffraction_order=2,
+        fourier_orders=5,
+        show_progress=True,
+        live_plot=True,
+        live_plot_x_key="energy_ev",
+        max_workers="auto",
+        on_error="fail_fast",
+        backend="numba",
+    )
 
-results = list(runner.run_cases(cases))
+    results = list(runner.run_cases(cases))
 
-csv_path = output_dir / "energy_angle_multilayer_all_orders.csv"
-plot_path = output_dir / "energy_angle_multilayer_fast.png"
-profile_path = output_dir / "energy_angle_multilayer_profile.png"
+    csv_path = output_dir / f"energy_angle_multilayer_all_orders_{args.solver}.csv"
+    plot_path = output_dir / f"energy_angle_multilayer_fast_{args.solver}.png"
+    profile_path = output_dir / "energy_angle_multilayer_profile.png"
 
-grax.write_all_orders_csv(results, csv_path)
-grating.plot_profile(profile_path)
+    grax.write_all_orders_csv(results, csv_path)
+    grating.plot_profile(profile_path)
 
-successful_results = [result for result in results if result.status == "ok"]
-figure, axis = plt.subplots(figsize=(10, 6))
-axis.plot(
-    [result.energy_ev for result in successful_results],
-    [result.selected_efficiency for result in successful_results],
-    "o-",
-    linewidth=1.0,
-    markersize=2.0,
-)
-axis.set_xlabel("Energy (eV)")
-axis.set_ylabel("Efficiency (2nd order)")
-axis.set_title("Fast Multilayer Energy-Angle Sweep (grax)")
-axis.grid(True, alpha=0.3)
-figure.tight_layout()
-figure.savefig(plot_path, dpi=150, bbox_inches="tight")
-plt.close(figure)
-
-print(f"Sampled {len(energy_angle_pairs)} energy-angle pairs from: {input_path}")
-print(f"Results saved to: {csv_path}")
-print(f"Plot saved to: {plot_path}")
-print(f"Profile plot saved to: {profile_path}")
+    successful_results = [result for result in results if result.status == "ok"]
+    figure, axis = plt.subplots(figsize=(10, 6))
+    axis.plot(
+        [result.energy_ev for result in successful_results],
+        [result.selected_efficiency for result in successful_results],
+        "o-",
+        linewidth=1.0,
+        markersize=2.0,
+    )
+    axis.set_xlabel("Energy (eV)")
+    axis.set_ylabel("Efficiency (2nd order)")
+    axis.set_title("Fast Multilayer Energy-Angle Sweep (grax)")
+    axis.grid(True, alpha=0.3)
+    figure.tight_layout()
+    figure.savefig(plot_path, dpi=150, bbox_inches="tight")
+    plt.close(figure)
+
+    print(f"Sampled {len(energy_angle_pairs)} energy-angle pairs from: {input_path}")
+    print(f"Results saved to: {csv_path}")
+    print(f"Plot saved to: {plot_path}")
+    print(f"Profile plot saved to: {profile_path}")
diff --git a/examples/simulation/energy_angle_sweep/polarization_comparison.py b/examples/simulation/energy_angle_sweep/polarization_comparison.py
index 6861345..ecc7cfe 100644
--- a/examples/simulation/energy_angle_sweep/polarization_comparison.py
+++ b/examples/simulation/energy_angle_sweep/polarization_comparison.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import argparse
 from pathlib import Path
 
 import matplotlib.pyplot as plt
@@ -45,53 +46,67 @@
     z_resolution_nm=1.0,
 )
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=2,
-    default_fourier_orders=5,
-    show_progress=True,
-    live_plot=False,
-    on_error="fail_fast",
-    backend="numba",
+parser = argparse.ArgumentParser(description="Polarization comparison (s vs p)")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
 )
+args = parser.parse_args()
 
-results_s = list(runner.run_cases(
-    grax.energy_angle_cases(grating=grating, energy_angle_pairs=energy_angle_pairs, polarization="s")
-))
-results_p = list(runner.run_cases(
-    grax.energy_angle_cases(grating=grating, energy_angle_pairs=energy_angle_pairs, polarization="p")
-))
+if __name__ == "__main__":
+    runner = grax.BatchSimulationRunner(
+        solver=args.solver,
+        diffraction_order=2,
+        fourier_orders=5,
+        show_progress=True,
+        live_plot=True,
+        live_plot_x_key="energy_ev",
+        max_workers="auto",
+        on_error="fail_fast",
+        backend="numba",
+    )
 
-ok_s = [r for r in results_s if r.status == "ok"]
-ok_p = [r for r in results_p if r.status == "ok"]
+    results_s = list(runner.run_cases(
+        grax.energy_angle_cases(grating=grating, energy_angle_pairs=energy_angle_pairs, polarization="s")
+    ))
+    results_p = list(runner.run_cases(
+        grax.energy_angle_cases(grating=grating, energy_angle_pairs=energy_angle_pairs, polarization="p")
+    ))
 
-comparison_plot_path = output_dir / "energy_angle_pol_comparison.png"
-figure, axis = plt.subplots(figsize=(10, 6))
-axis.plot(
-    [r.energy_ev for r in ok_s],
-    [r.selected_efficiency for r in ok_s],
-    "o-",
-    linewidth=1.5,
-    markersize=3,
-    color="tab:blue",
-    label="s (TE)",
-)
-axis.plot(
-    [r.energy_ev for r in ok_p],
-    [r.selected_efficiency for r in ok_p],
-    "s--",
-    linewidth=1.5,
-    markersize=3,
-    color="tab:orange",
-    label="p (TM)",
-)
-axis.set_xlabel("Energy (eV)")
-axis.set_ylabel("Efficiency (2nd order)")
-axis.set_title("Energy-Angle Sweep: s vs p Polarization")
-axis.grid(True, alpha=0.3)
-axis.legend(loc="best")
-figure.tight_layout()
-figure.savefig(comparison_plot_path, dpi=150, bbox_inches="tight")
-plt.close(figure)
+    ok_s = [r for r in results_s if r.status == "ok"]
+    ok_p = [r for r in results_p if r.status == "ok"]
+
+    comparison_plot_path = output_dir / f"energy_angle_pol_comparison_{args.solver}.png"
+    figure, axis = plt.subplots(figsize=(10, 6))
+    axis.plot(
+        [r.energy_ev for r in ok_s],
+        [r.selected_efficiency for r in ok_s],
+        "o-",
+        linewidth=1.5,
+        markersize=3,
+        color="tab:blue",
+        label="s (TE)",
+    )
+    axis.plot(
+        [r.energy_ev for r in ok_p],
+        [r.selected_efficiency for r in ok_p],
+        "s--",
+        linewidth=1.5,
+        markersize=3,
+        color="tab:orange",
+        label="p (TM)",
+    )
+    axis.set_xlabel("Energy (eV)")
+    axis.set_ylabel("Efficiency (2nd order)")
+    axis.set_title("Energy-Angle Sweep: s vs p Polarization")
+    axis.grid(True, alpha=0.3)
+    axis.legend(loc="best")
+    figure.tight_layout()
+    figure.savefig(comparison_plot_path, dpi=150, bbox_inches="tight")
+    plt.close(figure)
 
-print(f"Sampled {len(energy_angle_pairs)} energy-angle pairs from: {input_path}")
-print(f"Polarization comparison plot saved to: {comparison_plot_path}")
+    print(f"Sampled {len(energy_angle_pairs)} energy-angle pairs from: {input_path}")
+    print(f"Polarization comparison plot saved to: {comparison_plot_path}")
diff --git a/examples/simulation/energy_angle_sweep/results/energy_angle_multilayer_all_orders.csv b/examples/simulation/energy_angle_sweep/results/energy_angle_multilayer_all_orders.csv
deleted file mode 100644
index d1cd823..0000000
--- a/examples/simulation/energy_angle_sweep/results/energy_angle_multilayer_all_orders.csv
+++ /dev/null
@@ -1,386 +0,0 @@
-case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
-energy-angle-multilayer-00000000,500.0,14.17636,-5,3.4707454141672296e-07,19.98346586030081
-energy-angle-multilayer-00000000,500.0,14.17636,-4,3.4740166992260555e-06,18.960584473633418
-energy-angle-multilayer-00000000,500.0,14.17636,-3,0.00016274196236994713,17.88154389115782
-energy-angle-multilayer-00000000,500.0,14.17636,-2,0.010888087178155419,16.735473054396437
-energy-angle-multilayer-00000000,500.0,14.17636,-1,7.371719916647125e-05,15.507505003914389
-energy-angle-multilayer-00000000,500.0,14.17636,0,1.2150156310859254e-05,14.176360000000017
-energy-angle-multilayer-00000000,500.0,14.17636,1,1.4882913559956291e-08,12.709645440376349
-energy-angle-multilayer-00000000,500.0,14.17636,2,1.204462254070417e-05,11.053508139757653
-energy-angle-multilayer-00000000,500.0,14.17636,3,5.5693370930152245e-05,9.105145158871807
-energy-angle-multilayer-00000000,500.0,14.17636,4,6.116722109128628e-05,6.61102028673325
-energy-angle-multilayer-00000000,500.0,14.17636,5,1.7653202228598015e-05,2.141361994584713
-energy-angle-multilayer-00000001,600.0,11.48285,-5,2.534102516100492e-06,17.217434643588163
-energy-angle-multilayer-00000001,600.0,11.48285,-4,1.793745363338833e-05,16.22998735658038
-energy-angle-multilayer-00000001,600.0,11.48285,-3,0.0012486631310133767,15.18026708625976
-energy-angle-multilayer-00000001,600.0,11.48285,-2,0.03511668638660065,14.054319236430771
-energy-angle-multilayer-00000001,600.0,11.48285,-1,0.001403249355132933,12.832085101777267
-energy-angle-multilayer-00000001,600.0,11.48285,0,0.00035013867343425996,11.48285
-energy-angle-multilayer-00000001,600.0,11.48285,1,2.1506437699303084e-07,9.955098068131477
-energy-angle-multilayer-00000001,600.0,11.48285,2,0.00039215667366324254,8.149023861673356
-energy-angle-multilayer-00000001,600.0,11.48285,3,0.0007252648588694932,5.810633712874164
-energy-angle-multilayer-00000001,600.0,11.48285,4,0.0002456437901442845,1.0836902879969728
-energy-angle-multilayer-00000001,600.0,11.48285,5,0.0,0.0
-energy-angle-multilayer-00000002,700.0,9.73352,-5,4.159846249203512e-06,15.344753505465874
-energy-angle-multilayer-00000002,700.0,9.73352,-4,1.0777312823264536e-05,14.395715086871604
-energy-angle-multilayer-00000002,700.0,9.73352,-3,0.0012262542027451592,13.381043444064417
-energy-angle-multilayer-00000002,700.0,9.73352,-2,0.04639277986292073,12.284480161633468
-energy-angle-multilayer-00000002,700.0,9.73352,-1,0.0012289260941975879,11.081735492791452
-energy-angle-multilayer-00000002,700.0,9.73352,0,0.0002696016537936395,9.733519999999999
-energy-angle-multilayer-00000002,700.0,9.73352,1,5.82525932533489e-06,8.168106613077157
-energy-angle-multilayer-00000002,700.0,9.73352,2,0.0004187983661783736,6.223695611873339
-energy-angle-multilayer-00000002,700.0,9.73352,3,0.0012845965568395105,3.284895736426151
-energy-angle-multilayer-00000002,700.0,9.73352,4,0.0,0.0
-energy-angle-multilayer-00000002,700.0,9.73352,5,0.0,0.0
-energy-angle-multilayer-00000003,800.0,8.39171,-5,6.838260817764594e-06,13.904774687613326
-energy-angle-multilayer-00000003,800.0,8.39171,-4,7.129791583152668e-06,12.988330904529121
-energy-angle-multilayer-00000003,800.0,8.39171,-3,0.0012973895529614235,12.003400618302749
-energy-angle-multilayer-00000003,800.0,8.39171,-2,0.07265031227328393,10.931483264985445
-energy-angle-multilayer-00000003,800.0,8.39171,-1,0.001289246370302674,9.743908207012069
-energy-angle-multilayer-00000003,800.0,8.39171,0,0.00024019615323226818,8.39170999999999
-energy-angle-multilayer-00000003,800.0,8.39171,1,2.2055117701236576e-05,6.777048291515598
-energy-angle-multilayer-00000003,800.0,8.39171,2,0.0008492536098895093,4.633186429520947
-energy-angle-multilayer-00000003,800.0,8.39171,3,0.0,0.0
-energy-angle-multilayer-00000003,800.0,8.39171,4,0.0,0.0
-energy-angle-multilayer-00000003,800.0,8.39171,5,0.0,0.0
-energy-angle-multilayer-00000004,900.0,7.33737000000001,-5,1.1226188463637819e-05,12.765990268552713
-energy-angle-multilayer-00000004,900.0,7.33737000000001,-4,5.037315919776234e-06,11.87835260089426
-energy-angle-multilayer-00000004,900.0,7.33737000000001,-3,0.0012062208026834592,10.919906174735587
-energy-angle-multilayer-00000004,900.0,7.33737000000001,-2,0.10040557550419711,9.870041220327877
-energy-angle-multilayer-00000004,900.0,7.33737000000001,-1,0.0014186397031746743,8.695704937462423
-energy-angle-multilayer-00000004,900.0,7.33737000000001,0,0.00019661208409027983,7.33736999999995
-energy-angle-multilayer-00000004,900.0,7.33737000000001,1,3.816334714515429e-05,5.664167377869319
-energy-angle-multilayer-00000004,900.0,7.33737000000001,2,0.0016177074933441276,3.2175458436899618
-energy-angle-multilayer-00000004,900.0,7.33737000000001,3,0.0,0.0
-energy-angle-multilayer-00000004,900.0,7.33737000000001,4,0.0,0.0
-energy-angle-multilayer-00000004,900.0,7.33737000000001,5,0.0,0.0
-energy-angle-multilayer-00000005,1000.0,6.48506999999999,-5,1.7454652338631046e-05,11.840185664590607
-energy-angle-multilayer-00000005,1000.0,6.48506999999999,-4,3.5730867078845674e-06,10.978341877756137
-energy-angle-multilayer-00000005,1000.0,6.48506999999999,-3,0.001095604913093935,10.043786535512481
-energy-angle-multilayer-00000005,1000.0,6.48506999999999,-2,0.1310195560189737,9.01392934259222
-energy-angle-multilayer-00000005,1000.0,6.48506999999999,-1,0.0015187263871699458,7.851354411582506
-energy-angle-multilayer-00000005,1000.0,6.48506999999999,0,0.00014407579029771347,6.485069999999908
-energy-angle-multilayer-00000005,1000.0,6.48506999999999,1,9.928545127896339e-05,4.74214888245892
-energy-angle-multilayer-00000005,1000.0,6.48506999999999,2,0.003502435313222908,1.7144238199959858
-energy-angle-multilayer-00000005,1000.0,6.48506999999999,3,0.0,0.0
-energy-angle-multilayer-00000005,1000.0,6.48506999999999,4,0.0,0.0
-energy-angle-multilayer-00000005,1000.0,6.48506999999999,5,0.0,0.0
-energy-angle-multilayer-00000006,1100.0,5.78433,-5,1.0880971089040717e-05,11.073017887849176
-energy-angle-multilayer-00000006,1100.0,5.78433,-4,2.7449344054157534e-06,10.234681519378412
-energy-angle-multilayer-00000006,1100.0,5.78433,-3,0.0010094449487433523,9.322119191604628
-energy-angle-multilayer-00000006,1100.0,5.78433,-2,0.1636815471721913,8.310913974492266
-energy-angle-multilayer-00000006,1100.0,5.78433,-1,0.0015814998825647813,7.159387209945621
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-energy-angle-multilayer-00000006,1100.0,5.78433,2,0.0,0.0
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-energy-angle-multilayer-00000006,1100.0,5.78433,4,0.0,0.0
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-energy-angle-multilayer-00000007,1200.0,5.19929,-5,1.023733131387929e-06,10.426611332108465
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-energy-angle-multilayer-00000007,1200.0,5.19929,3,0.0,0.0
-energy-angle-multilayer-00000007,1200.0,5.19929,4,0.0,0.0
-energy-angle-multilayer-00000007,1200.0,5.19929,5,0.0,0.0
-energy-angle-multilayer-00000008,1300.0,4.70332999999999,-5,1.768844016053316e-06,9.873641967794498
-energy-angle-multilayer-00000008,1300.0,4.70332999999999,-4,1.4145356877030574e-06,9.077014218655194
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-energy-angle-multilayer-00000008,1300.0,4.70332999999999,-2,0.23064935165443318,7.2272866667668865
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-energy-angle-multilayer-00000008,1300.0,4.70332999999999,5,0.0,0.0
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-energy-angle-multilayer-00000009,1400.0,4.27764000000001,1,0.0021038353208859724,2.082262629550115
-energy-angle-multilayer-00000009,1400.0,4.27764000000001,2,0.0,0.0
-energy-angle-multilayer-00000009,1400.0,4.27764000000001,3,0.0,0.0
-energy-angle-multilayer-00000009,1400.0,4.27764000000001,4,0.0,0.0
-energy-angle-multilayer-00000009,1400.0,4.27764000000001,5,0.0,0.0
-energy-angle-multilayer-00000010,1500.0,3.9131,-5,8.295423184441386e-07,8.977277578958436
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-energy-angle-multilayer-00000011,1600.0,3.59097,-3,0.0005918864499395439,7.041550423339956
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-energy-angle-multilayer-00000011,1600.0,3.59097,0,0.00014060471751682323,3.590970000000155
-energy-angle-multilayer-00000011,1600.0,3.59097,1,0.006592108669032244,0.8250980968124253
-energy-angle-multilayer-00000011,1600.0,3.59097,2,0.0,0.0
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-energy-angle-multilayer-00000012,1700.0,3.30718,-5,1.0414869911789758e-06,8.277235567357664
-energy-angle-multilayer-00000012,1700.0,3.30718,-4,2.6853911245283452e-09,7.548781808334553
-energy-angle-multilayer-00000012,1700.0,3.30718,-3,0.0006387395540992631,6.742576394063633
-energy-angle-multilayer-00000012,1700.0,3.30718,-2,0.3537797973955303,5.82643184756931
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diff --git a/examples/simulation/energy_angle_sweep/results/energy_angle_multilayer_all_orders_rcwa.csv b/examples/simulation/energy_angle_sweep/results/energy_angle_multilayer_all_orders_rcwa.csv
new file mode 100644
index 0000000..52e13e2
--- /dev/null
+++ b/examples/simulation/energy_angle_sweep/results/energy_angle_multilayer_all_orders_rcwa.csv
@@ -0,0 +1,386 @@
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diff --git a/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_baseline_sigma_0p0_order_spectrum.png b/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_baseline_sigma_0p0_order_spectrum.png
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diff --git a/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_debye-waller_sigma_1p0_grating.pdf b/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_debye-waller_sigma_1p0_grating.pdf
index f12656e..a6ec32b 100644
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diff --git a/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_debye-waller_sigma_1p0_order_spectrum.png b/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_debye-waller_sigma_1p0_order_spectrum.png
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diff --git a/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_order1_comparison.png b/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_order1_comparison.png
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diff --git a/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_random-interface_sigma_1p0_supercells_10_grating.pdf b/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_random-interface_sigma_1p0_supercells_10_grating.pdf
index c6893a8..d885dd6 100644
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diff --git a/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_random-interface_sigma_1p0_supercells_3_grating.pdf b/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_random-interface_sigma_1p0_supercells_3_grating.pdf
index 2296949..e3c191e 100644
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diff --git a/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_random-interface_sigma_1p0_supercells_3_order_spectrum.png b/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_random-interface_sigma_1p0_supercells_3_order_spectrum.png
index 863bd77..24d0e3c 100644
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diff --git a/examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/roughness_kind_comparison_baseline_sigma_0p0_all_orders.csv b/examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/roughness_kind_comparison_baseline_sigma_0p0_all_orders.csv
index 6e9a982..ade8f10 100644
--- a/examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/roughness_kind_comparison_baseline_sigma_0p0_all_orders.csv
+++ b/examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/roughness_kind_comparison_baseline_sigma_0p0_all_orders.csv
@@ -1,25 +1,20 @@
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 fixed-00000004,250.0,1.0,2,0.0,0.0
 fixed-00000004,250.0,1.0,3,0.0,0.0
@@ -199,32 +92,84 @@ fixed-00000004,250.0,1.0,12,0.0,0.0
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@@ -240,32 +185,22 @@ fixed-00000005,300.0,1.0,12,0.0,0.0
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@@ -281,32 +216,22 @@ fixed-00000006,350.0,1.0,12,0.0,0.0
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-fixed-00000041,2100.0,1.0,-11,1.6524944387611234e-05,4.250128441543538
-fixed-00000041,2100.0,1.0,-10,1.1007666271396756e-05,4.06346465721623
-fixed-00000041,2100.0,1.0,-9,2.5198228097442967e-05,3.8678185799451796
-fixed-00000041,2100.0,1.0,-8,9.737534040167195e-05,3.661750727078541
-fixed-00000041,2100.0,1.0,-7,7.904595425108432e-05,3.443390546684313
-fixed-00000041,2100.0,1.0,-6,8.647250062131485e-06,3.2102306386705237
-fixed-00000041,2100.0,1.0,-5,0.00026914683791392466,2.9587742822905767
-fixed-00000041,2100.0,1.0,-4,0.00041133689785240304,2.6838837408036937
-fixed-00000041,2100.0,1.0,-3,0.0004494334154363566,2.377444168047276
-fixed-00000041,2100.0,1.0,-2,0.003820530760955193,2.025184372977648
-fixed-00000041,2100.0,1.0,-1,0.01892402830284893,1.597067571577469
-fixed-00000041,2100.0,1.0,0,0.054878792115801836,1.0000000000002558
+fixed-00000041,2100.0,1.0,-15,3.76467227763058e-06,4.926682676009079
+fixed-00000041,2100.0,1.0,-14,3.847420919261778e-06,4.766536061449884
+fixed-00000041,2100.0,1.0,-13,4.7509087386418986e-07,4.60083169098786
+fixed-00000041,2100.0,1.0,-12,1.2834406875673713e-05,4.42894579307756
+fixed-00000041,2100.0,1.0,-11,1.653007281635193e-05,4.250128441543538
+fixed-00000041,2100.0,1.0,-10,1.0852111803357905e-05,4.06346465721623
+fixed-00000041,2100.0,1.0,-9,2.5436343295056175e-05,3.8678185799451796
+fixed-00000041,2100.0,1.0,-8,9.748295163398372e-05,3.661750727078541
+fixed-00000041,2100.0,1.0,-7,7.878519656490273e-05,3.443390546684313
+fixed-00000041,2100.0,1.0,-6,8.736345527355589e-06,3.2102306386705237
+fixed-00000041,2100.0,1.0,-5,0.00026938793167857766,2.9587742822905767
+fixed-00000041,2100.0,1.0,-4,0.00041145348925751205,2.6838837408036937
+fixed-00000041,2100.0,1.0,-3,0.0004498430628934721,2.377444168047276
+fixed-00000041,2100.0,1.0,-2,0.0038219582848044316,2.025184372977648
+fixed-00000041,2100.0,1.0,-1,0.018919768793126172,1.597067571577469
+fixed-00000041,2100.0,1.0,0,0.05487129368561072,1.0000000000002558
 fixed-00000041,2100.0,1.0,1,0.0,0.0
 fixed-00000041,2100.0,1.0,2,0.0,0.0
 fixed-00000041,2100.0,1.0,3,0.0,0.0
@@ -1716,32 +1301,22 @@ fixed-00000041,2100.0,1.0,12,0.0,0.0
 fixed-00000041,2100.0,1.0,13,0.0,0.0
 fixed-00000041,2100.0,1.0,14,0.0,0.0
 fixed-00000041,2100.0,1.0,15,0.0,0.0
-fixed-00000041,2100.0,1.0,16,0.0,0.0
-fixed-00000041,2100.0,1.0,17,0.0,0.0
-fixed-00000041,2100.0,1.0,18,0.0,0.0
-fixed-00000041,2100.0,1.0,19,0.0,0.0
-fixed-00000041,2100.0,1.0,20,0.0,0.0
-fixed-00000042,2150.0,1.0,-20,2.087777242153461e-06,5.59583798986354
-fixed-00000042,2150.0,1.0,-19,1.0533026671474462e-06,5.458628371528434
-fixed-00000042,2150.0,1.0,-18,9.481832694592925e-08,5.317890695687026
-fixed-00000042,2150.0,1.0,-17,1.5182832741498116e-06,5.173337031902179
-fixed-00000042,2150.0,1.0,-16,9.586689532084963e-07,5.024638042683122
-fixed-00000042,2150.0,1.0,-15,5.865144692319015e-07,4.871414134793213
-fixed-00000042,2150.0,1.0,-14,2.5677603657993737e-06,4.713224019937556
-fixed-00000042,2150.0,1.0,-13,2.181430650654902e-07,4.549549692744549
-fixed-00000042,2150.0,1.0,-12,4.065228374986869e-06,4.379776351024617
-fixed-00000042,2150.0,1.0,-11,1.1218284210746925e-05,4.203165006905408
-fixed-00000042,2150.0,1.0,-10,3.4541641298365946e-06,4.018814247514484
-fixed-00000042,2150.0,1.0,-9,1.4336139293617905e-05,3.825605377674407
-fixed-00000042,2150.0,1.0,-8,5.239773465283891e-05,3.6221211606904404
-fixed-00000042,2150.0,1.0,-7,3.2787228120291885e-05,3.4065207361132224
-fixed-00000042,2150.0,1.0,-6,1.0435679357966083e-05,3.1763378209342505
-fixed-00000042,2150.0,1.0,-5,0.00013799169753491415,2.928135407144495
-fixed-00000042,2150.0,1.0,-4,0.00015411211684043753,2.656868181463466
-fixed-00000042,2150.0,1.0,-3,0.0001638860630062289,2.354577805992875
-fixed-00000042,2150.0,1.0,-2,0.0015985724317195181,2.0072970067893436
-fixed-00000042,2150.0,1.0,-1,0.00463934161326489,1.585737178457066
-fixed-00000042,2150.0,1.0,0,0.0316137250672733,0.999999999999531
+fixed-00000042,2150.0,1.0,-15,6.323678758381636e-07,4.871414134793213
+fixed-00000042,2150.0,1.0,-14,2.337181170716383e-06,4.713224019937556
+fixed-00000042,2150.0,1.0,-13,1.9749061703864317e-07,4.549549692744549
+fixed-00000042,2150.0,1.0,-12,4.263728629017924e-06,4.379776351024617
+fixed-00000042,2150.0,1.0,-11,1.1186518878996458e-05,4.203165006905408
+fixed-00000042,2150.0,1.0,-10,3.2953650640489095e-06,4.018814247514484
+fixed-00000042,2150.0,1.0,-9,1.4562217783996685e-05,3.825605377674407
+fixed-00000042,2150.0,1.0,-8,5.2330748078036395e-05,3.6221211606904404
+fixed-00000042,2150.0,1.0,-7,3.272093513988789e-05,3.4065207361132224
+fixed-00000042,2150.0,1.0,-6,1.0475658204955575e-05,3.1763378209342505
+fixed-00000042,2150.0,1.0,-5,0.00013809482263881873,2.928135407144495
+fixed-00000042,2150.0,1.0,-4,0.00015430679441357715,2.656868181463466
+fixed-00000042,2150.0,1.0,-3,0.00016423156515044826,2.354577805992875
+fixed-00000042,2150.0,1.0,-2,0.0015992170880653207,2.0072970067893436
+fixed-00000042,2150.0,1.0,-1,0.004637186248687532,1.585737178457066
+fixed-00000042,2150.0,1.0,0,0.031600578273110136,0.999999999999531
 fixed-00000042,2150.0,1.0,1,0.0,0.0
 fixed-00000042,2150.0,1.0,2,0.0,0.0
 fixed-00000042,2150.0,1.0,3,0.0,0.0
@@ -1757,8 +1332,3 @@ fixed-00000042,2150.0,1.0,12,0.0,0.0
 fixed-00000042,2150.0,1.0,13,0.0,0.0
 fixed-00000042,2150.0,1.0,14,0.0,0.0
 fixed-00000042,2150.0,1.0,15,0.0,0.0
-fixed-00000042,2150.0,1.0,16,0.0,0.0
-fixed-00000042,2150.0,1.0,17,0.0,0.0
-fixed-00000042,2150.0,1.0,18,0.0,0.0
-fixed-00000042,2150.0,1.0,19,0.0,0.0
-fixed-00000042,2150.0,1.0,20,0.0,0.0
diff --git a/examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/roughness_kind_comparison_debye-waller_sigma_1p0_all_orders.csv b/examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/roughness_kind_comparison_debye-waller_sigma_1p0_all_orders.csv
index a40ad42..06236b8 100644
--- a/examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/roughness_kind_comparison_debye-waller_sigma_1p0_all_orders.csv
+++ b/examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/roughness_kind_comparison_debye-waller_sigma_1p0_all_orders.csv
@@ -1,25 +1,20 @@
 case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
-fixed-00000000,50.0,1.0,-20,2.2984947196965812e-05,36.72836394252599
-fixed-00000000,50.0,1.0,-19,1.965650810536468e-05,35.76724513732081
-fixed-00000000,50.0,1.0,-18,1.9228475090940343e-05,34.783202072369875
-fixed-00000000,50.0,1.0,-17,2.0929107115017837e-05,33.77419865672606
-fixed-00000000,50.0,1.0,-16,2.545064311160859e-05,32.73789413681997
-fixed-00000000,50.0,1.0,-15,3.01487092675007e-05,31.671575132118377
-fixed-00000000,50.0,1.0,-14,2.447902304360026e-05,30.572066870934492
-fixed-00000000,50.0,1.0,-13,4.155633618105487e-05,29.435615277774055
-fixed-00000000,50.0,1.0,-12,5.0136916744268154e-05,28.25772728984554
-fixed-00000000,50.0,1.0,-11,2.8279977225790392e-05,27.03294976457456
-fixed-00000000,50.0,1.0,-10,8.469327377391509e-05,25.75455539976224
-fixed-00000000,50.0,1.0,-9,8.544753898909452e-05,24.41408289662344
-fixed-00000000,50.0,1.0,-8,3.6943662858318034e-05,23.00063908061179
-fixed-00000000,50.0,1.0,-7,0.00021909651145910906,21.49979251955007
-fixed-00000000,50.0,1.0,-6,0.00014772364744213302,19.891721918786743
-fixed-00000000,50.0,1.0,-5,0.00010894471593747758,18.147895381206368
-fixed-00000000,50.0,1.0,-4,0.0007853482911749062,16.224541946816103
-fixed-00000000,50.0,1.0,-3,0.0002652479580067044,14.048051607021762
-fixed-00000000,50.0,1.0,-2,0.0012880936000371993,11.47520357492894
-fixed-00000000,50.0,1.0,-1,0.009167218541255542,8.138281537089384
-fixed-00000000,50.0,1.0,0,0.9141069728530385,0.9999999999999005
+fixed-00000000,50.0,1.0,-15,4.9649624186436795e-05,31.671575132118377
+fixed-00000000,50.0,1.0,-14,3.0381763505142203e-05,30.572066870934492
+fixed-00000000,50.0,1.0,-13,4.583640081854475e-05,29.435615277774055
+fixed-00000000,50.0,1.0,-12,5.717164702119044e-05,28.25772728984554
+fixed-00000000,50.0,1.0,-11,3.046073834991317e-05,27.03294976457456
+fixed-00000000,50.0,1.0,-10,8.810969138248851e-05,25.75455539976224
+fixed-00000000,50.0,1.0,-9,9.091350223285952e-05,24.41408289662344
+fixed-00000000,50.0,1.0,-8,3.763186443500154e-05,23.00063908061179
+fixed-00000000,50.0,1.0,-7,0.00022295677765669732,21.49979251955007
+fixed-00000000,50.0,1.0,-6,0.00015281815818299365,19.891721918786743
+fixed-00000000,50.0,1.0,-5,0.00010829939827472735,18.147895381206368
+fixed-00000000,50.0,1.0,-4,0.0007913225225700919,16.224541946816103
+fixed-00000000,50.0,1.0,-3,0.00027033205706694305,14.048051607021762
+fixed-00000000,50.0,1.0,-2,0.0012855398166847646,11.47520357492894
+fixed-00000000,50.0,1.0,-1,0.009184130218578683,8.138281537089384
+fixed-00000000,50.0,1.0,0,0.9141239248854857,0.9999999999999005
 fixed-00000000,50.0,1.0,1,0.0,0.0
 fixed-00000000,50.0,1.0,2,0.0,0.0
 fixed-00000000,50.0,1.0,3,0.0,0.0
@@ -35,73 +30,22 @@ fixed-00000000,50.0,1.0,12,0.0,0.0
 fixed-00000000,50.0,1.0,13,0.0,0.0
 fixed-00000000,50.0,1.0,14,0.0,0.0
 fixed-00000000,50.0,1.0,15,0.0,0.0
-fixed-00000000,50.0,1.0,16,0.0,0.0
-fixed-00000000,50.0,1.0,17,0.0,0.0
-fixed-00000000,50.0,1.0,18,0.0,0.0
-fixed-00000000,50.0,1.0,19,0.0,0.0
-fixed-00000000,50.0,1.0,20,0.0,0.0
-fixed-00000001,100.0,1.0,-20,0.0002873188864256795,25.75455539976224
-fixed-00000001,100.0,1.0,-19,0.0002597472937158553,25.092692345474617
-fixed-00000001,100.0,1.0,-18,0.00015895884880084458,24.41408289662344
-fixed-00000001,100.0,1.0,-17,0.00023067008771372998,23.71728455090644
-fixed-00000001,100.0,1.0,-16,0.0002529390710592117,23.00063908061179
-fixed-00000001,100.0,1.0,-15,0.000189372546828792,22.262224525633528
-fixed-00000001,100.0,1.0,-14,0.00026919644898512716,21.49979251955007
-fixed-00000001,100.0,1.0,-13,0.00027629006106702215,20.710685071056957
-fixed-00000001,100.0,1.0,-12,0.0002743386890561856,19.891721918786743
-fixed-00000001,100.0,1.0,-11,0.00030452645505614116,19.039044648764516
-fixed-00000001,100.0,1.0,-10,0.0003598270927401174,18.147895381206368
-fixed-00000001,100.0,1.0,-9,0.00046213285551844984,17.212292967831786
-fixed-00000001,100.0,1.0,-8,0.0002999406164646781,16.224541946816103
-fixed-00000001,100.0,1.0,-7,0.0007364037967326692,15.174454773733487
-fixed-00000001,100.0,1.0,-6,0.0008362784976020872,14.048051607021762
-fixed-00000001,100.0,1.0,-5,0.0003277209539417367,12.825231674657005
-fixed-00000001,100.0,1.0,-4,0.002670562568839844,11.47520357492894
-fixed-00000001,100.0,1.0,-3,0.0015809683185932764,9.946291914593857
-fixed-00000001,100.0,1.0,-2,0.0032837314590831936,8.138281537089384
-fixed-00000001,100.0,1.0,-1,0.03171512724680363,5.795583718663309
-fixed-00000001,100.0,1.0,0,0.910920921048948,0.9999999999999005
-fixed-00000001,100.0,1.0,1,0.0,0.0
-fixed-00000001,100.0,1.0,2,0.0,0.0
-fixed-00000001,100.0,1.0,3,0.0,0.0
-fixed-00000001,100.0,1.0,4,0.0,0.0
-fixed-00000001,100.0,1.0,5,0.0,0.0
-fixed-00000001,100.0,1.0,6,0.0,0.0
-fixed-00000001,100.0,1.0,7,0.0,0.0
-fixed-00000001,100.0,1.0,8,0.0,0.0
-fixed-00000001,100.0,1.0,9,0.0,0.0
-fixed-00000001,100.0,1.0,10,0.0,0.0
-fixed-00000001,100.0,1.0,11,0.0,0.0
-fixed-00000001,100.0,1.0,12,0.0,0.0
-fixed-00000001,100.0,1.0,13,0.0,0.0
-fixed-00000001,100.0,1.0,14,0.0,0.0
-fixed-00000001,100.0,1.0,15,0.0,0.0
-fixed-00000001,100.0,1.0,16,0.0,0.0
-fixed-00000001,100.0,1.0,17,0.0,0.0
-fixed-00000001,100.0,1.0,18,0.0,0.0
-fixed-00000001,100.0,1.0,19,0.0,0.0
-fixed-00000001,100.0,1.0,20,0.0,0.0
-fixed-00000002,150.0,1.0,-20,0.000132058903865966,20.976868904814538
-fixed-00000002,150.0,1.0,-19,0.00014401552505121477,20.441189450923062
-fixed-00000002,150.0,1.0,-18,0.00011351319931724601,19.891721918786743
-fixed-00000002,150.0,1.0,-17,0.00015364004854167757,19.32728860142933
-fixed-00000002,150.0,1.0,-16,0.00019493288378006208,18.74653592772742
-fixed-00000002,150.0,1.0,-15,0.00015694622904226032,18.147895381206368
-fixed-00000002,150.0,1.0,-14,0.00023410678340764177,17.529532494186512
-fixed-00000002,150.0,1.0,-13,0.00029918542851710097,16.889279144628944
-fixed-00000002,150.0,1.0,-12,0.0002657636128503786,16.224541946816103
-fixed-00000002,150.0,1.0,-11,0.0004081855135301806,15.532175532332047
-fixed-00000002,150.0,1.0,-10,0.0005292313144237513,14.808302728188039
-fixed-00000002,150.0,1.0,-9,0.0005453615691113501,14.048051607021762
-fixed-00000002,150.0,1.0,-8,0.0006807336885632796,13.245156988362638
-fixed-00000002,150.0,1.0,-7,0.0009994706783218762,12.3913297567059
-fixed-00000002,150.0,1.0,-6,0.001249047144694422,11.47520357492894
-fixed-00000002,150.0,1.0,-5,0.0008005490551356587,10.480450869119537
-fixed-00000002,150.0,1.0,-4,0.003471104208057602,9.382091896469547
-fixed-00000002,150.0,1.0,-3,0.003076022278893972,8.138281537089384
-fixed-00000002,150.0,1.0,-2,0.0040513188383636016,6.668112195698512
-fixed-00000002,150.0,1.0,-1,0.05313702807804421,4.766536061449884
-fixed-00000002,150.0,1.0,0,0.8471805729171162,0.9999999999999005
+fixed-00000002,150.0,1.0,-15,0.00023829936673733058,18.147895381206368
+fixed-00000002,150.0,1.0,-14,0.000283607336075577,17.529532494186512
+fixed-00000002,150.0,1.0,-13,0.00032150251198085456,16.889279144628944
+fixed-00000002,150.0,1.0,-12,0.0002996800339647527,16.224541946816103
+fixed-00000002,150.0,1.0,-11,0.0004413498962023356,15.532175532332047
+fixed-00000002,150.0,1.0,-10,0.0005459003324883759,14.808302728188039
+fixed-00000002,150.0,1.0,-9,0.0005758252623688087,14.048051607021762
+fixed-00000002,150.0,1.0,-8,0.0007158387893772929,13.245156988362638
+fixed-00000002,150.0,1.0,-7,0.0010050113977948783,12.3913297567059
+fixed-00000002,150.0,1.0,-6,0.0012836009540934832,11.47520357492894
+fixed-00000002,150.0,1.0,-5,0.0008279508095290992,10.480450869119537
+fixed-00000002,150.0,1.0,-4,0.0034478994456011306,9.382091896469547
+fixed-00000002,150.0,1.0,-3,0.003128566090372503,8.138281537089384
+fixed-00000002,150.0,1.0,-2,0.0040005909995595905,6.668112195698512
+fixed-00000002,150.0,1.0,-1,0.05306224695490669,4.766536061449884
+fixed-00000002,150.0,1.0,0,0.8476589436872426,0.9999999999999005
 fixed-00000002,150.0,1.0,1,0.0,0.0
 fixed-00000002,150.0,1.0,2,0.0,0.0
 fixed-00000002,150.0,1.0,3,0.0,0.0
@@ -117,73 +61,22 @@ fixed-00000002,150.0,1.0,12,0.0,0.0
 fixed-00000002,150.0,1.0,13,0.0,0.0
 fixed-00000002,150.0,1.0,14,0.0,0.0
 fixed-00000002,150.0,1.0,15,0.0,0.0
-fixed-00000002,150.0,1.0,16,0.0,0.0
-fixed-00000002,150.0,1.0,17,0.0,0.0
-fixed-00000002,150.0,1.0,18,0.0,0.0
-fixed-00000002,150.0,1.0,19,0.0,0.0
-fixed-00000002,150.0,1.0,20,0.0,0.0
-fixed-00000003,200.0,1.0,-20,9.951648958266715e-05,18.147895381206368
-fixed-00000003,200.0,1.0,-19,0.00010561169883067181,17.68608429287241
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 fixed-00000004,250.0,1.0,3,0.0,0.0
@@ -199,32 +92,84 @@ fixed-00000004,250.0,1.0,12,0.0,0.0
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 fixed-00000006,350.0,1.0,2,0.0,0.0
 fixed-00000006,350.0,1.0,3,0.0,0.0
@@ -281,32 +216,22 @@ fixed-00000006,350.0,1.0,12,0.0,0.0
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-fixed-00000040,2050.0,1.0,-9,2.7486679966630457e-05,3.9116022974194777
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-fixed-00000040,2050.0,1.0,-4,0.0005257197771840076,2.711928222677855
-fixed-00000040,2050.0,1.0,-3,0.0008078202477920409,2.4011921598898454
-fixed-00000040,2050.0,1.0,-2,0.009092487169708115,2.0437761763499083
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-fixed-00000040,2050.0,1.0,0,0.12382032159896206,0.9999999999999005
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+fixed-00000040,2050.0,1.0,-9,2.8019073943803077e-05,3.9116022974194777
+fixed-00000040,2050.0,1.0,-8,0.00012212219614764357,3.7028584136860587
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+fixed-00000040,2050.0,1.0,-6,8.820727512933782e-06,3.2453969058251175
+fixed-00000040,2050.0,1.0,-5,0.0002477703634934023,2.9905708104901265
+fixed-00000040,2050.0,1.0,-4,0.0005258688682442734,2.711928222677855
+fixed-00000040,2050.0,1.0,-3,0.0008085878833757247,2.4011921598898454
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+fixed-00000040,2050.0,1.0,-1,0.017490261052543483,1.6088649635830876
+fixed-00000040,2050.0,1.0,0,0.12380253743571254,0.9999999999999005
 fixed-00000040,2050.0,1.0,1,0.0,0.0
 fixed-00000040,2050.0,1.0,2,0.0,0.0
 fixed-00000040,2050.0,1.0,3,0.0,0.0
@@ -1675,32 +1270,22 @@ fixed-00000040,2050.0,1.0,12,0.0,0.0
 fixed-00000040,2050.0,1.0,13,0.0,0.0
 fixed-00000040,2050.0,1.0,14,0.0,0.0
 fixed-00000040,2050.0,1.0,15,0.0,0.0
-fixed-00000040,2050.0,1.0,16,0.0,0.0
-fixed-00000040,2050.0,1.0,17,0.0,0.0
-fixed-00000040,2050.0,1.0,18,0.0,0.0
-fixed-00000040,2050.0,1.0,19,0.0,0.0
-fixed-00000040,2050.0,1.0,20,0.0,0.0
-fixed-00000041,2100.0,1.0,-20,8.780391412243527e-07,5.660010570330854
-fixed-00000041,2100.0,1.0,-19,7.236558779909692e-07,5.5211204660151765
-fixed-00000041,2100.0,1.0,-18,1.283501999266982e-07,5.378656453875905
-fixed-00000041,2100.0,1.0,-17,1.0966361681606384e-06,5.232326612394644
-fixed-00000041,2100.0,1.0,-16,8.879448400935884e-07,5.081797001742743
-fixed-00000041,2100.0,1.0,-15,2.8678808207097014e-06,4.926682676009079
-fixed-00000041,2100.0,1.0,-14,3.294621246092799e-06,4.766536061449884
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-fixed-00000041,2100.0,1.0,-12,9.653190572986256e-06,4.42894579307756
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-fixed-00000041,2100.0,1.0,-9,1.91209040930472e-05,3.8678185799451796
-fixed-00000041,2100.0,1.0,-8,7.389029647831203e-05,3.661750727078541
-fixed-00000041,2100.0,1.0,-7,5.9981602846580897e-05,3.443390546684313
-fixed-00000041,2100.0,1.0,-6,6.561701023866478e-06,3.2102306386705237
-fixed-00000041,2100.0,1.0,-5,0.00020423383956990633,2.9587742822905767
-fixed-00000041,2100.0,1.0,-4,0.0003121304142240652,2.6838837408036937
-fixed-00000041,2100.0,1.0,-3,0.00034103879048706843,2.377444168047276
-fixed-00000041,2100.0,1.0,-2,0.0028990928243948213,2.025184372977648
-fixed-00000041,2100.0,1.0,-1,0.014359919627428244,1.597067571577469
-fixed-00000041,2100.0,1.0,0,0.04164309159877017,1.0000000000002558
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+fixed-00000041,2100.0,1.0,-8,7.397195396805341e-05,3.661750727078541
+fixed-00000041,2100.0,1.0,-7,5.978373485801748e-05,3.443390546684313
+fixed-00000041,2100.0,1.0,-6,6.629308390507006e-06,3.2102306386705237
+fixed-00000041,2100.0,1.0,-5,0.00020441678619351552,2.9587742822905767
+fixed-00000041,2100.0,1.0,-4,0.00031221888604305746,2.6838837408036937
+fixed-00000041,2100.0,1.0,-3,0.0003413496389209018,2.377444168047276
+fixed-00000041,2100.0,1.0,-2,0.0029001760571723914,2.025184372977648
+fixed-00000041,2100.0,1.0,-1,0.0143566874288555,1.597067571577469
+fixed-00000041,2100.0,1.0,0,0.04163740164454092,1.0000000000002558
 fixed-00000041,2100.0,1.0,1,0.0,0.0
 fixed-00000041,2100.0,1.0,2,0.0,0.0
 fixed-00000041,2100.0,1.0,3,0.0,0.0
@@ -1716,32 +1301,22 @@ fixed-00000041,2100.0,1.0,12,0.0,0.0
 fixed-00000041,2100.0,1.0,13,0.0,0.0
 fixed-00000041,2100.0,1.0,14,0.0,0.0
 fixed-00000041,2100.0,1.0,15,0.0,0.0
-fixed-00000041,2100.0,1.0,16,0.0,0.0
-fixed-00000041,2100.0,1.0,17,0.0,0.0
-fixed-00000041,2100.0,1.0,18,0.0,0.0
-fixed-00000041,2100.0,1.0,19,0.0,0.0
-fixed-00000041,2100.0,1.0,20,0.0,0.0
-fixed-00000042,2150.0,1.0,-20,1.5633165893301074e-06,5.59583798986354
-fixed-00000042,2150.0,1.0,-19,7.887074827191813e-07,5.458628371528434
-fixed-00000042,2150.0,1.0,-18,7.099946320623868e-08,5.317890695687026
-fixed-00000042,2150.0,1.0,-17,1.1368825092338872e-06,5.173337031902179
-fixed-00000042,2150.0,1.0,-16,7.178462567590384e-07,5.024638042683122
-fixed-00000042,2150.0,1.0,-15,4.391789416607586e-07,4.871414134793213
-fixed-00000042,2150.0,1.0,-14,1.9227254211938774e-06,4.713224019937556
-fixed-00000042,2150.0,1.0,-13,1.6334437677481439e-07,4.549549692744549
-fixed-00000042,2150.0,1.0,-12,3.0440215697903023e-06,4.379776351024617
-fixed-00000042,2150.0,1.0,-11,8.4001920589915e-06,4.203165006905408
-fixed-00000042,2150.0,1.0,-10,2.586459885381595e-06,4.018814247514484
-fixed-00000042,2150.0,1.0,-9,1.0734825503482856e-05,3.825605377674407
-fixed-00000042,2150.0,1.0,-8,3.923514739609324e-05,3.6221211606904404
-fixed-00000042,2150.0,1.0,-7,2.4550903517720826e-05,3.4065207361132224
-fixed-00000042,2150.0,1.0,-6,7.81418167218386e-06,3.1763378209342505
-fixed-00000042,2150.0,1.0,-5,0.00010332745543468139,2.928135407144495
-fixed-00000042,2150.0,1.0,-4,0.00011539834040193385,2.656868181463466
-fixed-00000042,2150.0,1.0,-3,0.00012271701974937255,2.354577805992875
-fixed-00000042,2150.0,1.0,-2,0.001197002607028705,2.0072970067893436
-fixed-00000042,2150.0,1.0,-1,0.0034739145351089114,1.585737178457066
-fixed-00000042,2150.0,1.0,0,0.023672190619920864,0.999999999999531
+fixed-00000042,2150.0,1.0,-15,4.735137307261522e-07,4.871414134793213
+fixed-00000042,2150.0,1.0,-14,1.7500689358421103e-06,4.713224019937556
+fixed-00000042,2150.0,1.0,-13,1.4787993260003943e-07,4.549549692744549
+fixed-00000042,2150.0,1.0,-12,3.1926575132460833e-06,4.379776351024617
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+fixed-00000042,2150.0,1.0,-10,2.4675519823239164e-06,4.018814247514484
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+fixed-00000042,2150.0,1.0,-8,3.918498820212523e-05,3.6221211606904404
+fixed-00000042,2150.0,1.0,-7,2.4501263683580855e-05,3.4065207361132224
+fixed-00000042,2150.0,1.0,-6,7.844117621986866e-06,3.1763378209342505
+fixed-00000042,2150.0,1.0,-5,0.00010340467496866966,2.928135407144495
+fixed-00000042,2150.0,1.0,-4,0.0001155441139420965,2.656868181463466
+fixed-00000042,2150.0,1.0,-3,0.0001229757299330079,2.354577805992875
+fixed-00000042,2150.0,1.0,-2,0.001197485322300939,2.0072970067893436
+fixed-00000042,2150.0,1.0,-1,0.003472300609479392,1.585737178457066
+fixed-00000042,2150.0,1.0,0,0.023662346369779222,0.999999999999531
 fixed-00000042,2150.0,1.0,1,0.0,0.0
 fixed-00000042,2150.0,1.0,2,0.0,0.0
 fixed-00000042,2150.0,1.0,3,0.0,0.0
@@ -1757,8 +1332,3 @@ fixed-00000042,2150.0,1.0,12,0.0,0.0
 fixed-00000042,2150.0,1.0,13,0.0,0.0
 fixed-00000042,2150.0,1.0,14,0.0,0.0
 fixed-00000042,2150.0,1.0,15,0.0,0.0
-fixed-00000042,2150.0,1.0,16,0.0,0.0
-fixed-00000042,2150.0,1.0,17,0.0,0.0
-fixed-00000042,2150.0,1.0,18,0.0,0.0
-fixed-00000042,2150.0,1.0,19,0.0,0.0
-fixed-00000042,2150.0,1.0,20,0.0,0.0
diff --git a/examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/roughness_kind_comparison_random-interface_sigma_1p0_supercells_3_all_orders.csv b/examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/roughness_kind_comparison_random-interface_sigma_1p0_supercells_3_all_orders.csv
index 7b41bc9..5f228a4 100644
--- a/examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/roughness_kind_comparison_random-interface_sigma_1p0_supercells_3_all_orders.csv
+++ b/examples/simulation/fixed_angle_roughness/results_roughness_kind_comparison/roughness_kind_comparison_random-interface_sigma_1p0_supercells_3_all_orders.csv
@@ -1,35 +1,29 @@
 case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
-fixed-00000000,50.0,1.0,-10,0.00011136829574085792,25.75455539976224
-fixed-00000000,50.0,1.0,-9.666666666666666,1.1548485692053952e-06,25.31510829004378
-fixed-00000000,50.0,1.0,-9.333333333333334,1.3712460801791148e-06,24.868417150378832
-fixed-00000000,50.0,1.0,-9,9.133100294990068e-05,24.41408289662344
-fixed-00000000,50.0,1.0,-8.666666666666666,1.5757338124031759e-06,23.95166910189785
-fixed-00000000,50.0,1.0,-8.333333333333334,1.9344001470195816e-06,23.480696919147036
-fixed-00000000,50.0,1.0,-8,4.8478903521669875e-05,23.00063908061179
-fixed-00000000,50.0,1.0,-7.666666666666667,2.0728854329041587e-06,22.510912760477325
-fixed-00000000,50.0,1.0,-7.333333333333333,1.9489977077764655e-06,22.01087102590685
-fixed-00000000,50.0,1.0,-7,0.00022095650897649215,21.49979251955007
-fixed-00000000,50.0,1.0,-6.666666666666667,2.8061524263388745e-06,20.976868904814538
-fixed-00000000,50.0,1.0,-6.333333333333333,2.539444200167902e-06,20.441189450923048
-fixed-00000000,50.0,1.0,-6,0.0001497810421057474,19.891721918786743
-fixed-00000000,50.0,1.0,-5.666666666666667,1.4234292694521606e-06,19.32728860142933
-fixed-00000000,50.0,1.0,-5.333333333333333,2.163416469070816e-06,18.746535927727408
-fixed-00000000,50.0,1.0,-5,0.00011383343818317847,18.147895381206368
-fixed-00000000,50.0,1.0,-4.666666666666667,2.8651235524867604e-06,17.529532494186512
-fixed-00000000,50.0,1.0,-4.333333333333333,1.6570562868083411e-06,16.88927914462893
-fixed-00000000,50.0,1.0,-4,0.0007873948198112612,16.224541946816103
-fixed-00000000,50.0,1.0,-3.6666666666666665,1.5065598001434514e-06,15.532175532332019
-fixed-00000000,50.0,1.0,-3.3333333333333335,8.915482766638045e-07,14.808302728188025
-fixed-00000000,50.0,1.0,-3,0.00027369482527769113,14.048051607021762
-fixed-00000000,50.0,1.0,-2.6666666666666665,4.128146302660248e-06,13.24515698836261
-fixed-00000000,50.0,1.0,-2.3333333333333335,2.7785779262995555e-06,12.391329756705872
-fixed-00000000,50.0,1.0,-2,0.0013055875323541822,11.47520357492894
-fixed-00000000,50.0,1.0,-1.6666666666666667,1.158108014822446e-06,10.480450869119494
-fixed-00000000,50.0,1.0,-1.3333333333333333,2.6891316537628046e-06,9.382091896469447
-fixed-00000000,50.0,1.0,-1,0.009213022342051068,8.138281537089384
-fixed-00000000,50.0,1.0,-0.6666666666666666,9.523457133007622e-07,6.668112195698512
-fixed-00000000,50.0,1.0,-0.3333333333333333,1.7156598869070365e-06,4.766536061449727
-fixed-00000000,50.0,1.0,0,0.9144572803092793,0.9999999999999005
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+fixed-00000000,50.0,1.0,-7.333333333333333,1.9241762141437386e-06,22.01087102590685
+fixed-00000000,50.0,1.0,-7,0.00014952459320665508,21.49979251955007
+fixed-00000000,50.0,1.0,-6.666666666666667,3.336263455076302e-06,20.976868904814538
+fixed-00000000,50.0,1.0,-6.333333333333333,4.419388855005009e-06,20.441189450923048
+fixed-00000000,50.0,1.0,-6,0.00018168017505826325,19.891721918786743
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+fixed-00000000,50.0,1.0,-4,0.0007919989722642087,16.224541946816103
+fixed-00000000,50.0,1.0,-3.6666666666666665,3.1562095744036444e-06,15.532175532332019
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+fixed-00000000,50.0,1.0,-3,0.00029365213109564556,14.048051607021762
+fixed-00000000,50.0,1.0,-2.6666666666666665,8.123934612252187e-07,13.24515698836261
+fixed-00000000,50.0,1.0,-2.3333333333333335,1.6499131172153515e-06,12.391329756705872
+fixed-00000000,50.0,1.0,-2,0.001207628748513242,11.47520357492894
+fixed-00000000,50.0,1.0,-1.6666666666666667,2.8292663600431874e-06,10.480450869119494
+fixed-00000000,50.0,1.0,-1.3333333333333333,5.495417374376698e-07,9.382091896469447
+fixed-00000000,50.0,1.0,-1,0.009336456888205134,8.138281537089384
+fixed-00000000,50.0,1.0,-0.6666666666666666,5.984515337233137e-07,6.668112195698512
+fixed-00000000,50.0,1.0,-0.3333333333333333,6.297135163358838e-07,4.766536061449727
+fixed-00000000,50.0,1.0,0,0.914664596994289,0.9999999999999005
 fixed-00000000,50.0,1.0,0.3333333333333333,0.0,0.0
 fixed-00000000,50.0,1.0,0.6666666666666666,0.0,0.0
 fixed-00000000,50.0,1.0,1,0.0,0.0
@@ -54,43 +48,31 @@ fixed-00000000,50.0,1.0,7,0.0,0.0
 fixed-00000000,50.0,1.0,7.333333333333333,0.0,0.0
 fixed-00000000,50.0,1.0,7.666666666666667,0.0,0.0
 fixed-00000000,50.0,1.0,8,0.0,0.0
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-fixed-00000000,50.0,1.0,8.666666666666666,0.0,0.0
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-fixed-00000000,50.0,1.0,9.666666666666666,0.0,0.0
-fixed-00000000,50.0,1.0,10,0.0,0.0
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-fixed-00000001,100.0,1.0,-9.666666666666666,5.688869769146544e-06,17.841305983032
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-fixed-00000001,100.0,1.0,-8.666666666666666,1.1295925455395695e-05,16.88927914462893
-fixed-00000001,100.0,1.0,-8.333333333333334,1.1981433267960783e-05,16.560152883804193
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@@ -115,43 +97,31 @@ fixed-00000001,100.0,1.0,7,0.0,0.0
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-fixed-00000042,2150.0,1.0,-6,2.507971905342516e-05,3.1763378209342505
-fixed-00000042,2150.0,1.0,-5.666666666666667,2.000829923759761e-05,3.0958134100880415
-fixed-00000042,2150.0,1.0,-5.333333333333333,1.920161909378884e-05,3.01313994701637
-fixed-00000042,2150.0,1.0,-5,0.00010676549814230693,2.928135407144495
-fixed-00000042,2150.0,1.0,-4.666666666666667,2.640414395144051e-05,2.840590525945103
-fixed-00000042,2150.0,1.0,-4.333333333333333,1.4107304514501613e-05,2.7502627256417895
-fixed-00000042,2150.0,1.0,-4,0.00011025734891856808,2.656868181463466
-fixed-00000042,2150.0,1.0,-3.6666666666666665,5.608578673397403e-05,2.560071279505152
-fixed-00000042,2150.0,1.0,-3.3333333333333335,2.3386093410923307e-05,2.4594703345799616
-fixed-00000042,2150.0,1.0,-3,0.00025789281469273647,2.354577805992875
-fixed-00000042,2150.0,1.0,-2.6666666666666665,3.5015994203037994e-05,2.244792174954071
-fixed-00000042,2150.0,1.0,-2.3333333333333335,3.556514856831739e-05,2.1293567382343497
-fixed-00000042,2150.0,1.0,-2,0.0015956984286436835,2.0072970067893436
-fixed-00000042,2150.0,1.0,-1.6666666666666667,1.9196294246111306e-05,1.8773213290066906
-fixed-00000042,2150.0,1.0,-1.3333333333333333,4.890379735386529e-05,1.737654285092475
-fixed-00000042,2150.0,1.0,-1,0.004184588655239029,1.585737178457066
-fixed-00000042,2150.0,1.0,-0.6666666666666666,5.167596933210395e-05,1.4176372333809297
-fixed-00000042,2150.0,1.0,-0.3333333333333333,4.629961376873392e-05,1.226719687901749
-fixed-00000042,2150.0,1.0,0,0.02716341077427635,0.999999999999531
-fixed-00000042,2150.0,1.0,0.3333333333333333,6.196384987979451e-05,0.7036844083900036
+fixed-00000042,2150.0,1.0,-8,2.6994170828631805e-05,3.6221211606904404
+fixed-00000042,2150.0,1.0,-7.666666666666667,1.6005114187199576e-05,3.5517070102008717
+fixed-00000042,2150.0,1.0,-7.333333333333333,3.332837267372938e-05,3.4798702026836708
+fixed-00000042,2150.0,1.0,-7,5.690102026663515e-05,3.4065207361132224
+fixed-00000042,2150.0,1.0,-6.666666666666667,1.136639504968769e-05,3.3315587012155135
+fixed-00000042,2150.0,1.0,-6.333333333333333,1.256209552315199e-05,3.2548726839852122
+fixed-00000042,2150.0,1.0,-6,5.234336293109305e-05,3.1763378209342505
+fixed-00000042,2150.0,1.0,-5.666666666666667,1.3722260898860623e-05,3.0958134100880415
+fixed-00000042,2150.0,1.0,-5.333333333333333,3.7585226438251073e-06,3.01313994701637
+fixed-00000042,2150.0,1.0,-5,8.947101646492861e-05,2.928135407144495
+fixed-00000042,2150.0,1.0,-4.666666666666667,5.65273989166552e-05,2.840590525945103
+fixed-00000042,2150.0,1.0,-4.333333333333333,4.731830450809035e-05,2.7502627256417895
+fixed-00000042,2150.0,1.0,-4,8.5159003392611e-05,2.656868181463466
+fixed-00000042,2150.0,1.0,-3.6666666666666665,2.687540776207718e-05,2.560071279505152
+fixed-00000042,2150.0,1.0,-3.3333333333333335,3.633836900164145e-05,2.4594703345799616
+fixed-00000042,2150.0,1.0,-3,0.00023582395185857034,2.354577805992875
+fixed-00000042,2150.0,1.0,-2.6666666666666665,1.9141419469119848e-05,2.244792174954071
+fixed-00000042,2150.0,1.0,-2.3333333333333335,3.0346820061442737e-05,2.1293567382343497
+fixed-00000042,2150.0,1.0,-2,0.0011280199669844373,2.0072970067893436
+fixed-00000042,2150.0,1.0,-1.6666666666666667,2.978326374636978e-05,1.8773213290066906
+fixed-00000042,2150.0,1.0,-1.3333333333333333,6.70619927925125e-06,1.737654285092475
+fixed-00000042,2150.0,1.0,-1,0.0038682995524157316,1.585737178457066
+fixed-00000042,2150.0,1.0,-0.6666666666666666,6.233553349739382e-05,1.4176372333809297
+fixed-00000042,2150.0,1.0,-0.3333333333333333,2.6874295437439765e-05,1.226719687901749
+fixed-00000042,2150.0,1.0,0,0.02783738907312455,0.999999999999531
+fixed-00000042,2150.0,1.0,0.3333333333333333,7.898134359638344e-05,0.7036844083900036
 fixed-00000042,2150.0,1.0,0.6666666666666666,0.0,0.0
 fixed-00000042,2150.0,1.0,1,0.0,0.0
 fixed-00000042,2150.0,1.0,1.3333333333333333,0.0,0.0
@@ -2616,9 +2106,3 @@ fixed-00000042,2150.0,1.0,7,0.0,0.0
 fixed-00000042,2150.0,1.0,7.333333333333333,0.0,0.0
 fixed-00000042,2150.0,1.0,7.666666666666667,0.0,0.0
 fixed-00000042,2150.0,1.0,8,0.0,0.0
-fixed-00000042,2150.0,1.0,8.333333333333334,0.0,0.0
-fixed-00000042,2150.0,1.0,8.666666666666666,0.0,0.0
-fixed-00000042,2150.0,1.0,9,0.0,0.0
-fixed-00000042,2150.0,1.0,9.333333333333334,0.0,0.0
-fixed-00000042,2150.0,1.0,9.666666666666666,0.0,0.0
-fixed-00000042,2150.0,1.0,10,0.0,0.0
diff --git a/examples/simulation/fixed_angle_roughness/roughness_correlation.py b/examples/simulation/fixed_angle_roughness/roughness_correlation.py
index 581b5ca..659b682 100644
--- a/examples/simulation/fixed_angle_roughness/roughness_correlation.py
+++ b/examples/simulation/fixed_angle_roughness/roughness_correlation.py
@@ -43,10 +43,10 @@
 # reproducible run to run); set an explicit int to reproduce one specific
 # ensemble for debugging.
 ROUGHNESS_SEED: int | None = None
-# Number of independent roughness realizations averaged per simulated point
-# (see ``RoughnessSpec.num_realizations``). The library default (8) is
-# usually fine as-is; exposed here for visibility/override.
-ROUGHNESS_NUM_REALIZATIONS = 8
+# Number of independent roughness realizations averaged per simulated point.
+# Two retains ensemble averaging while keeping the supercell study usable as
+# a runnable demonstration.
+ROUGHNESS_NUM_REALIZATIONS = 2
 
 # In addition to the single-period random-interface sweep above, also run the
 # same correlation-length sweep with the roughness spanning several grating
@@ -60,7 +60,7 @@
 ENERGIES_EV = np.arange(50.0, 2200.0, 50.0)
 POLARIZATION = "p"
 DIFFRACTION_ORDER = 1
-FOURIER_ORDERS = 20
+FOURIER_ORDERS = 15
 # Fourier orders used for the supercell runs. Solver cost scales with
 # fourier_orders * num_supercells, so this is set low enough that the
 # effective order count (here 4 * 5 = 20) matches the single-period runs
@@ -78,6 +78,9 @@
 WIDTH_TO_PERIOD_RATIO = 0.67
 DEPTH_NM = 14.9
 WALL_ANGLE_DEG = 15.0
+# 1 nm random-interface roughness needs sub-0.25 nm sampling for its
+# generated interface field; this intentionally exceeds the normal example
+# resolution floor.
 X_RESOLUTION_NM = 0.1
 Z_RESOLUTION_NM = 0.1
 
@@ -153,6 +156,12 @@ def main() -> None:
     PLOTS_DIR.mkdir(parents=True, exist_ok=True)
 
     parser = argparse.ArgumentParser(description="Run the roughness correlation-length comparison example.")
+    parser.add_argument(
+        "--solver",
+        choices=("rcwa", "neviere"),
+        default="rcwa",
+        help="Electromagnetic solver to run.",
+    )
     parser.add_argument(
         "--geometry-only",
         action="store_true",
@@ -191,8 +200,9 @@ def main() -> None:
 
         fourier_orders = FOURIER_ORDERS if num_supercells == 1 else SUPERCELL_FOURIER_ORDERS
         runner = grax.BatchSimulationRunner(
-            default_diffraction_order=DIFFRACTION_ORDER,
-            default_fourier_orders=fourier_orders,
+            solver=args.solver,
+            diffraction_order=DIFFRACTION_ORDER,
+            fourier_orders=fourier_orders,
             show_progress=True,
             live_plot=True,
             live_plot_x_key="energy_ev",
diff --git a/examples/simulation/fixed_angle_roughness/roughness_kind_comparison.py b/examples/simulation/fixed_angle_roughness/roughness_kind_comparison.py
index f04f9db..b459beb 100644
--- a/examples/simulation/fixed_angle_roughness/roughness_kind_comparison.py
+++ b/examples/simulation/fixed_angle_roughness/roughness_kind_comparison.py
@@ -47,16 +47,16 @@
 # a fixed sigma.
 DEBYE_SIGMA_NM = 1.0
 RANDOM_INTERFACE_SIGMA_NM = 1.0
-RANDOM_INTERFACE_NUM_SUPERCELLS = [10] # [1, 5, 10]
+RANDOM_INTERFACE_NUM_SUPERCELLS = [3]  # [1, 3, 5, 10]
 # Base seed for the random-interface roughness ensemble. ``None`` draws real
 # entropy (a genuinely random surface each run, so results are not
 # reproducible run to run); set an explicit int to reproduce one specific
 # ensemble for debugging.
 ROUGHNESS_SEED: int | None = None
-# Number of independent roughness realizations averaged per simulated point
-# (see ``RoughnessSpec.num_realizations``). The library default (8) is
-# usually fine as-is; exposed here for visibility/override.
-ROUGHNESS_NUM_REALIZATIONS = 8
+# Number of independent roughness realizations averaged per simulated point.
+# Two retains ensemble averaging while keeping the 3-supercell example usable
+# as a runnable demonstration.
+ROUGHNESS_NUM_REALIZATIONS = 2
 # Lateral autocorrelation length of the "random-interface" roughness, in nm.
 # ``None`` defaults to one tenth of the grating period; ``0.0`` gives an
 # uncorrelated (white-noise) interface.
@@ -67,12 +67,11 @@
 ENERGIES_EV = np.arange(50.0, 2200.0, 50.0)
 POLARIZATION = "p"
 DIFFRACTION_ORDER = 1
-FOURIER_ORDERS = 20
+FOURIER_ORDERS = 15
 # Fourier orders used for the supercell runs (num_supercells > 1). Solver
-# cost scales with fourier_orders * num_supercells (and the solver hard-caps
-# around 100 effective orders), so this is set low enough that even the
-# largest supercell count here stays well within that limit.
-SUPERCELL_FOURIER_ORDERS = 20
+# cost scales with fourier_orders * num_supercells. The three-supercell
+# demonstration uses 24 effective orders, below the RCWA warning threshold.
+SUPERCELL_FOURIER_ORDERS = 8
 MAX_WORKERS = "auto"
 BACKEND = "numba"
 
@@ -85,6 +84,9 @@
 WIDTH_TO_PERIOD_RATIO = 0.67
 DEPTH_NM = 14.9
 WALL_ANGLE_DEG = 15.0
+# 1 nm random-interface roughness needs sub-0.25 nm sampling for its
+# generated interface field; this intentionally exceeds the normal example
+# resolution floor.
 X_RESOLUTION_NM = 0.1
 Z_RESOLUTION_NM = 0.1
 
@@ -160,6 +162,12 @@ def main() -> None:
     PLOTS_DIR.mkdir(parents=True, exist_ok=True)
 
     parser = argparse.ArgumentParser(description="Run the roughness-kind comparison example.")
+    parser.add_argument(
+        "--solver",
+        choices=("rcwa", "neviere"),
+        default="rcwa",
+        help="Electromagnetic solver to run.",
+    )
     parser.add_argument(
         "--geometry-only",
         action="store_true",
@@ -198,10 +206,11 @@ def main() -> None:
 
         fourier_orders = FOURIER_ORDERS if num_supercells == 1 else SUPERCELL_FOURIER_ORDERS
         runner = grax.BatchSimulationRunner(
-            default_diffraction_order=DIFFRACTION_ORDER,
-            default_fourier_orders=fourier_orders,
+            solver=args.solver,
+            diffraction_order=DIFFRACTION_ORDER,
+            fourier_orders=fourier_orders,
             show_progress=True,
-            live_plot=False,
+            live_plot=True,
             on_error="continue",
             max_workers=MAX_WORKERS,
             backend=BACKEND,
diff --git a/examples/simulation/fixed_angle_roughness/run_roughness_examples.sh b/examples/simulation/fixed_angle_roughness/run_roughness_examples.sh
index f487871..3245347 100755
--- a/examples/simulation/fixed_angle_roughness/run_roughness_examples.sh
+++ b/examples/simulation/fixed_angle_roughness/run_roughness_examples.sh
@@ -71,7 +71,9 @@ case "$MODE" in
         ;;
 esac
 
-if [[ -x "$SCRIPT_DIR/../../../.venv/bin/python" ]]; then
+if [[ -n "${PYTHON_BIN:-}" ]]; then
+    PYTHON="${PYTHON_BIN}"
+elif [[ -x "$SCRIPT_DIR/../../../.venv/bin/python" ]]; then
     PYTHON="$SCRIPT_DIR/../../../.venv/bin/python"
 else
     PYTHON="python3"
diff --git a/examples/simulation/fixed_angle_sweep/fixed_angle_sweep.py b/examples/simulation/fixed_angle_sweep/fixed_angle_sweep.py
index d96f82c..24cf26b 100644
--- a/examples/simulation/fixed_angle_sweep/fixed_angle_sweep.py
+++ b/examples/simulation/fixed_angle_sweep/fixed_angle_sweep.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import argparse
 from pathlib import Path
 
 import numpy as np
@@ -17,7 +18,7 @@
     layer_material="Pt",
     layer_thickness_nm=28.77,
     x_resolution_nm=0.5,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
 )
 
 output_dir = Path(__file__).resolve().parent / "results"
@@ -33,32 +34,45 @@
     polarization="p",
 )
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=20,
-    show_progress=True,
-    live_plot=True,
-    live_plot_x_key="energy_ev",
-    on_error="continue",
-    backend="numba",
+parser = argparse.ArgumentParser(description="Fixed-angle energy sweep")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
 )
+args = parser.parse_args()
 
-results = list(runner.run_cases(cases))
+if __name__ == "__main__":
+    runner = grax.BatchSimulationRunner(
+        solver=args.solver,
+        diffraction_order=1,
+        fourier_orders=15,
+        show_progress=True,
+        live_plot=True,
+        live_plot_x_key="energy_ev",
+        max_workers="auto",
+        on_error="continue",
+        backend="numba",
+    )
 
-csv_path = output_dir / "fixed_angle_all_orders.csv"
-grax.write_all_orders_csv(results, csv_path)
+    results = list(runner.run_cases(cases))
 
-orders_plot_path = output_dir / "fixed_angle_orders_1_3.png"
-grax.plot_order_subset(
-    results,
-    orders_plot_path,
-    diffraction_orders=[1, 2, 3],
-    title="Fixed-Angle Sweep: Orders 1-3 Efficiency vs Energy",
-)
+    csv_path = output_dir / f"fixed_angle_all_orders_{args.solver}.csv"
+    grax.write_all_orders_csv(results, csv_path)
+
+    orders_plot_path = output_dir / f"fixed_angle_orders_1_3_{args.solver}.png"
+    grax.plot_order_subset(
+        results,
+        orders_plot_path,
+        diffraction_orders=[1, 2, 3],
+        title="Fixed-Angle Sweep: Orders 1-3 Efficiency vs Energy",
+    )
 
-profile_path = output_dir / "fixed_angle_profile.png"
-grating.plot_profile(profile_path)
+    profile_path = output_dir / "fixed_angle_profile.png"
+    grating.plot_profile(profile_path)
 
-print(f"Results saved to: {csv_path}")
-print(f"Orders 1-3 plot saved to: {orders_plot_path}")
-print(f"Profile plot saved to: {profile_path}")
+    print(f"Results saved to: {csv_path}")
+    print(f"Orders 1-3 plot saved to: {orders_plot_path}")
+    print(f"Profile plot saved to: {profile_path}")
diff --git a/examples/simulation/fixed_angle_sweep/polarization_comparison.py b/examples/simulation/fixed_angle_sweep/polarization_comparison.py
index 8985466..3ea7c46 100644
--- a/examples/simulation/fixed_angle_sweep/polarization_comparison.py
+++ b/examples/simulation/fixed_angle_sweep/polarization_comparison.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import argparse
 from pathlib import Path
 
 import matplotlib.pyplot as plt
@@ -18,7 +19,7 @@
     layer_material="Pt",
     layer_thickness_nm=28.77,
     x_resolution_nm=0.5,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
 )
 
 output_dir = Path(__file__).resolve().parent / "results"
@@ -28,64 +29,78 @@
 energies_ev = np.arange(50.0, 650.0, 10)
 diffraction_orders = [1, 2, 3]
 
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=20,
-    show_progress=True,
-    live_plot=False,
-    on_error="continue",
-    backend="numba",
+parser = argparse.ArgumentParser(description="Polarization comparison (s vs p)")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
 )
-
-results_s = list(runner.run_cases(
-    grax.fixed_angle_cases(
-        grating=grating,
-        energies_ev=energies_ev,
-        grazing_angle_deg=grazing_angle_deg,
-        polarization="s",
-    )
-))
-results_p = list(runner.run_cases(
-    grax.fixed_angle_cases(
-        grating=grating,
-        energies_ev=energies_ev,
-        grazing_angle_deg=grazing_angle_deg,
-        polarization="p",
+args = parser.parse_args()
+
+if __name__ == "__main__":
+    runner = grax.BatchSimulationRunner(
+        solver=args.solver,
+        diffraction_order=1,
+        fourier_orders=15,
+        show_progress=True,
+        live_plot=True,
+        live_plot_x_key="energy_ev",
+        max_workers="auto",
+        on_error="continue",
+        backend="numba",
     )
-))
-
-
-def sorted_ok(results):
-    return sorted([r for r in results if r.status == "ok"], key=lambda r: float(r.energy_ev))
-
 
-collected_s = sorted_ok(results_s)
-collected_p = sorted_ok(results_p)
-energies = np.asarray([r.energy_ev for r in collected_s], dtype=float)
-
-comparison_plot_path = output_dir / "fixed_angle_pol_comparison.png"
-colors = ["tab:blue", "tab:orange", "tab:green"]
-
-figure, axis = plt.subplots(figsize=(10, 6))
-for index, order in enumerate(diffraction_orders):
-    eff_s = np.asarray(
-        [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in collected_s],
-        dtype=float,
-    )
-    eff_p = np.asarray(
-        [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in collected_p],
-        dtype=float,
-    )
-    axis.plot(energies, eff_s, "-", color=colors[index], linewidth=1.5, markersize=2, label=f"Order {order} (s)")
-    axis.plot(energies, eff_p, "--", color=colors[index], linewidth=1.5, markersize=2, label=f"Order {order} (p)")
-
-axis.set_xlabel("Photon Energy (eV)")
-axis.set_ylabel("Diffraction Efficiency")
-axis.set_title("Fixed-Angle Sweep: s vs p Polarization, Orders 1–3")
-axis.grid(True, alpha=0.3)
-axis.legend(loc="best")
-figure.tight_layout()
-figure.savefig(comparison_plot_path, dpi=150, bbox_inches="tight")
-plt.close(figure)
-
-print(f"Polarization comparison plot saved to: {comparison_plot_path}")
+    results_s = list(runner.run_cases(
+        grax.fixed_angle_cases(
+            grating=grating,
+            energies_ev=energies_ev,
+            grazing_angle_deg=grazing_angle_deg,
+            polarization="s",
+        )
+    ))
+    results_p = list(runner.run_cases(
+        grax.fixed_angle_cases(
+            grating=grating,
+            energies_ev=energies_ev,
+            grazing_angle_deg=grazing_angle_deg,
+            polarization="p",
+        )
+    ))
+
+
+    def sorted_ok(results):
+        return sorted([r for r in results if r.status == "ok"], key=lambda r: float(r.energy_ev))
+
+
+    collected_s = sorted_ok(results_s)
+    collected_p = sorted_ok(results_p)
+    energies = np.asarray([r.energy_ev for r in collected_s], dtype=float)
+
+    comparison_plot_path = output_dir / f"fixed_angle_pol_comparison_{args.solver}.png"
+    colors = ["tab:blue", "tab:orange", "tab:green"]
+
+    figure, axis = plt.subplots(figsize=(10, 6))
+    for index, order in enumerate(diffraction_orders):
+        eff_s = np.asarray(
+            [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in collected_s],
+            dtype=float,
+        )
+        eff_p = np.asarray(
+            [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in collected_p],
+            dtype=float,
+        )
+        axis.plot(energies, eff_s, "-", color=colors[index], linewidth=1.5, markersize=2, label=f"Order {order} (s)")
+        axis.plot(energies, eff_p, "--", color=colors[index], linewidth=1.5, markersize=2, label=f"Order {order} (p)")
+
+    axis.set_xlabel("Photon Energy (eV)")
+    axis.set_ylabel("Diffraction Efficiency")
+    axis.set_title("Fixed-Angle Sweep: s vs p Polarization, Orders 1–3")
+    axis.grid(True, alpha=0.3)
+    axis.legend(loc="best")
+    figure.tight_layout()
+    figure.savefig(comparison_plot_path, dpi=150, bbox_inches="tight")
+    plt.close(figure)
+
+    print(f"Polarization comparison plot saved to: {comparison_plot_path}")
diff --git a/examples/simulation/fixed_angle_sweep/results/fixed_angle_all_orders.csv b/examples/simulation/fixed_angle_sweep/results/fixed_angle_all_orders.csv
deleted file mode 100644
index 65c6e3b..0000000
--- a/examples/simulation/fixed_angle_sweep/results/fixed_angle_all_orders.csv
+++ /dev/null
@@ -1,2461 +0,0 @@
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diff --git a/examples/simulation/fixed_angle_sweep/results/fixed_angle_all_orders_rcwa.csv b/examples/simulation/fixed_angle_sweep/results/fixed_angle_all_orders_rcwa.csv
new file mode 100644
index 0000000..2481466
--- /dev/null
+++ b/examples/simulation/fixed_angle_sweep/results/fixed_angle_all_orders_rcwa.csv
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diff --git a/examples/simulation/fixed_angle_sweep/results/fixed_angle_orders_1_3.png b/examples/simulation/fixed_angle_sweep/results/fixed_angle_orders_1_3.png
deleted file mode 100644
index 082264c..0000000
Binary files a/examples/simulation/fixed_angle_sweep/results/fixed_angle_orders_1_3.png and /dev/null differ
diff --git a/examples/simulation/fixed_angle_sweep/results/fixed_angle_orders_1_3_rcwa.png b/examples/simulation/fixed_angle_sweep/results/fixed_angle_orders_1_3_rcwa.png
new file mode 100644
index 0000000..6cfb7ac
Binary files /dev/null and b/examples/simulation/fixed_angle_sweep/results/fixed_angle_orders_1_3_rcwa.png differ
diff --git a/examples/simulation/fixed_angle_sweep/results/fixed_angle_pol_comparison_rcwa.png b/examples/simulation/fixed_angle_sweep/results/fixed_angle_pol_comparison_rcwa.png
new file mode 100644
index 0000000..ac573ba
Binary files /dev/null and b/examples/simulation/fixed_angle_sweep/results/fixed_angle_pol_comparison_rcwa.png differ
diff --git a/examples/simulation/fixed_angle_sweep/results/fixed_angle_profile.png b/examples/simulation/fixed_angle_sweep/results/fixed_angle_profile.png
index e09c3b4..a68bbca 100644
Binary files a/examples/simulation/fixed_angle_sweep/results/fixed_angle_profile.png and b/examples/simulation/fixed_angle_sweep/results/fixed_angle_profile.png differ
diff --git a/examples/simulation/monochromator_sweep/monochromator_sweep.py b/examples/simulation/monochromator_sweep/monochromator_sweep.py
index 626b1ed..4fbfd15 100644
--- a/examples/simulation/monochromator_sweep/monochromator_sweep.py
+++ b/examples/simulation/monochromator_sweep/monochromator_sweep.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import argparse
 from pathlib import Path
 
 import numpy as np
@@ -15,7 +16,7 @@
     blaze_angle_deg=0.75,
     anti_blaze_angle_deg=5.597,
     x_resolution_nm=0.5,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
 )
 
 output_dir = Path(__file__).resolve().parent / "results"
@@ -31,31 +32,44 @@
     polarization="p",
 )
 
-runner = grax.BatchSimulationRunner(
-    default_fourier_orders=20,
-    show_progress=True,
-    live_plot=True,
-    live_plot_x_key="energy_ev",
-    on_error="continue",
-    backend="numba",
+parser = argparse.ArgumentParser(description="Monochromator energy sweep")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
 )
+args = parser.parse_args()
 
-results = list(runner.run_cases(cases))
+if __name__ == "__main__":
+    runner = grax.BatchSimulationRunner(
+        solver=args.solver,
+        fourier_orders=15,
+        show_progress=True,
+        live_plot=True,
+        live_plot_x_key="energy_ev",
+        max_workers="auto",
+        on_error="continue",
+        backend="numba",
+    )
 
-csv_path = output_dir / "monochromator_all_orders.csv"
-grax.write_all_orders_csv(results, csv_path)
+    results = list(runner.run_cases(cases))
 
-orders_plot_path = output_dir / "monochromator_orders_1_3.png"
-grax.plot_order_subset(
-    results,
-    orders_plot_path,
-    diffraction_orders=[1, 2, 3],
-    title="Monochromator Sweep: Orders 1-3 Efficiency vs Energy",
-)
+    csv_path = output_dir / f"monochromator_all_orders_{args.solver}.csv"
+    grax.write_all_orders_csv(results, csv_path)
+
+    orders_plot_path = output_dir / f"monochromator_orders_1_3_{args.solver}.png"
+    grax.plot_order_subset(
+        results,
+        orders_plot_path,
+        diffraction_orders=[1, 2, 3],
+        title="Monochromator Sweep: Orders 1-3 Efficiency vs Energy",
+    )
 
-profile_path = output_dir / "monochromator_profile.png"
-grating.plot_profile(profile_path)
+    profile_path = output_dir / "monochromator_profile.png"
+    grating.plot_profile(profile_path)
 
-print(f"Results saved to: {csv_path}")
-print(f"Orders 1-3 plot saved to: {orders_plot_path}")
-print(f"Profile plot saved to: {profile_path}")
+    print(f"Results saved to: {csv_path}")
+    print(f"Orders 1-3 plot saved to: {orders_plot_path}")
+    print(f"Profile plot saved to: {profile_path}")
diff --git a/examples/simulation/monochromator_sweep/polarization_comparison.py b/examples/simulation/monochromator_sweep/polarization_comparison.py
index 9742098..0adf183 100644
--- a/examples/simulation/monochromator_sweep/polarization_comparison.py
+++ b/examples/simulation/monochromator_sweep/polarization_comparison.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import argparse
 from pathlib import Path
 
 import matplotlib.pyplot as plt
@@ -16,7 +17,7 @@
     blaze_angle_deg=0.75,
     anti_blaze_angle_deg=5.597,
     x_resolution_nm=0.5,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
 )
 
 output_dir = Path(__file__).resolve().parent / "results"
@@ -25,65 +26,79 @@
 energies_ev = np.arange(50.0, 2000.1, 10)
 diffraction_orders = [1, 2, 3]
 
-runner = grax.BatchSimulationRunner(
-    default_fourier_orders=20,
-    show_progress=True,
-    live_plot=False,
-    on_error="continue",
-    backend="numba",
+parser = argparse.ArgumentParser(description="Polarization comparison (s vs p)")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
 )
-
-results_s = list(runner.run_cases(
-    grax.monochromator_cases(
-        grating=grating,
-        energies_ev=energies_ev,
-        diffraction_order=1,
-        cff=2.25,
-        polarization="s",
-    )
-))
-results_p = list(runner.run_cases(
-    grax.monochromator_cases(
-        grating=grating,
-        energies_ev=energies_ev,
-        diffraction_order=1,
-        cff=2.25,
-        polarization="p",
+args = parser.parse_args()
+
+if __name__ == "__main__":
+    runner = grax.BatchSimulationRunner(
+        solver=args.solver,
+        fourier_orders=15,
+        show_progress=True,
+        live_plot=True,
+        live_plot_x_key="energy_ev",
+        max_workers="auto",
+        on_error="continue",
+        backend="numba",
     )
-))
-
-
-def sorted_ok(results):
-    return sorted([r for r in results if r.status == "ok"], key=lambda r: float(r.energy_ev))
-
 
-collected_s = sorted_ok(results_s)
-collected_p = sorted_ok(results_p)
-energies = np.asarray([r.energy_ev for r in collected_s], dtype=float)
-
-comparison_plot_path = output_dir / "monochromator_pol_comparison.png"
-colors = ["tab:blue", "tab:orange", "tab:green"]
-
-figure, axis = plt.subplots(figsize=(10, 6))
-for index, order in enumerate(diffraction_orders):
-    eff_s = np.asarray(
-        [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in collected_s],
-        dtype=float,
-    )
-    eff_p = np.asarray(
-        [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in collected_p],
-        dtype=float,
-    )
-    axis.plot(energies, eff_s, "-", color=colors[index], linewidth=1.5, markersize=2, label=f"Order {order} (s)")
-    axis.plot(energies, eff_p, "--", color=colors[index], linewidth=1.5, markersize=2, label=f"Order {order} (p)")
-
-axis.set_xlabel("Photon Energy (eV)")
-axis.set_ylabel("Diffraction Efficiency")
-axis.set_title("Monochromator Sweep: s vs p Polarization, Orders 1–3")
-axis.grid(True, alpha=0.3)
-axis.legend(loc="best")
-figure.tight_layout()
-figure.savefig(comparison_plot_path, dpi=150, bbox_inches="tight")
-plt.close(figure)
-
-print(f"Polarization comparison plot saved to: {comparison_plot_path}")
+    results_s = list(runner.run_cases(
+        grax.monochromator_cases(
+            grating=grating,
+            energies_ev=energies_ev,
+            diffraction_order=1,
+            cff=2.25,
+            polarization="s",
+        )
+    ))
+    results_p = list(runner.run_cases(
+        grax.monochromator_cases(
+            grating=grating,
+            energies_ev=energies_ev,
+            diffraction_order=1,
+            cff=2.25,
+            polarization="p",
+        )
+    ))
+
+
+    def sorted_ok(results):
+        return sorted([r for r in results if r.status == "ok"], key=lambda r: float(r.energy_ev))
+
+
+    collected_s = sorted_ok(results_s)
+    collected_p = sorted_ok(results_p)
+    energies = np.asarray([r.energy_ev for r in collected_s], dtype=float)
+
+    comparison_plot_path = output_dir / f"monochromator_pol_comparison_{args.solver}.png"
+    colors = ["tab:blue", "tab:orange", "tab:green"]
+
+    figure, axis = plt.subplots(figsize=(10, 6))
+    for index, order in enumerate(diffraction_orders):
+        eff_s = np.asarray(
+            [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in collected_s],
+            dtype=float,
+        )
+        eff_p = np.asarray(
+            [grax.efficiency_for_order(r.orders, r.efficiency_all, diffraction_order=order) for r in collected_p],
+            dtype=float,
+        )
+        axis.plot(energies, eff_s, "-", color=colors[index], linewidth=1.5, markersize=2, label=f"Order {order} (s)")
+        axis.plot(energies, eff_p, "--", color=colors[index], linewidth=1.5, markersize=2, label=f"Order {order} (p)")
+
+    axis.set_xlabel("Photon Energy (eV)")
+    axis.set_ylabel("Diffraction Efficiency")
+    axis.set_title("Monochromator Sweep: s vs p Polarization, Orders 1–3")
+    axis.grid(True, alpha=0.3)
+    axis.legend(loc="best")
+    figure.tight_layout()
+    figure.savefig(comparison_plot_path, dpi=150, bbox_inches="tight")
+    plt.close(figure)
+
+    print(f"Polarization comparison plot saved to: {comparison_plot_path}")
diff --git a/examples/simulation/monochromator_sweep/results/monochromator_all_orders.csv b/examples/simulation/monochromator_sweep/results/monochromator_all_orders.csv
deleted file mode 100644
index 917c8ae..0000000
--- a/examples/simulation/monochromator_sweep/results/monochromator_all_orders.csv
+++ /dev/null
@@ -1,8037 +0,0 @@
-case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
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-mono-00000000,50.0,4.882210444916382,-10,1.0519915570222573e-05,32.048873041242494
-mono-00000000,50.0,4.882210444916382,-9,2.544577897233805e-05,30.40456269536064
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diff --git a/examples/simulation/monochromator_sweep/results/monochromator_all_orders_rcwa.csv b/examples/simulation/monochromator_sweep/results/monochromator_all_orders_rcwa.csv
new file mode 100644
index 0000000..13cb6cc
--- /dev/null
+++ b/examples/simulation/monochromator_sweep/results/monochromator_all_orders_rcwa.csv
@@ -0,0 +1,6077 @@
+case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
+mono-00000000,50.0,4.882210444916382,-15,1.2056598617554735e-06,39.35717589304749
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+mono-00000194,1990.0,0.777174591521657,12,0.0,0.0
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+mono-00000194,1990.0,0.777174591521657,15,0.0,0.0
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+mono-00000195,2000.0,0.7752296420774627,-14,6.237060488362667e-06,5.900841804034783
+mono-00000195,2000.0,0.7752296420774627,-13,7.752125994098108e-06,5.689793466757507
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diff --git a/examples/simulation/monochromator_sweep/results/monochromator_orders_1_3.png b/examples/simulation/monochromator_sweep/results/monochromator_orders_1_3.png
deleted file mode 100644
index 1f92fcf..0000000
Binary files a/examples/simulation/monochromator_sweep/results/monochromator_orders_1_3.png and /dev/null differ
diff --git a/examples/simulation/monochromator_sweep/results/monochromator_orders_1_3_rcwa.png b/examples/simulation/monochromator_sweep/results/monochromator_orders_1_3_rcwa.png
new file mode 100644
index 0000000..e3e6c53
Binary files /dev/null and b/examples/simulation/monochromator_sweep/results/monochromator_orders_1_3_rcwa.png differ
diff --git a/examples/simulation/monochromator_sweep/results/monochromator_pol_comparison_rcwa.png b/examples/simulation/monochromator_sweep/results/monochromator_pol_comparison_rcwa.png
new file mode 100644
index 0000000..54f4424
Binary files /dev/null and b/examples/simulation/monochromator_sweep/results/monochromator_pol_comparison_rcwa.png differ
diff --git a/examples/simulation/monochromator_sweep/results/monochromator_profile.png b/examples/simulation/monochromator_sweep/results/monochromator_profile.png
index 1a78c9a..b0087f7 100644
Binary files a/examples/simulation/monochromator_sweep/results/monochromator_profile.png and b/examples/simulation/monochromator_sweep/results/monochromator_profile.png differ
diff --git a/examples/simulation/multilayer_theta_search/multilayer_theta_search.py b/examples/simulation/multilayer_theta_search/multilayer_theta_search.py
index fdb69de..e4cb53d 100644
--- a/examples/simulation/multilayer_theta_search/multilayer_theta_search.py
+++ b/examples/simulation/multilayer_theta_search/multilayer_theta_search.py
@@ -2,6 +2,8 @@
 
 from __future__ import annotations
 
+import argparse
+
 import logging
 from pathlib import Path
 
@@ -63,49 +65,65 @@
     z_resolution_nm=1.0,
 )
 
-sweep = grax.run_multilayer_theta_search_sweep(
-    grating=grating,
-    energies_ev=energies_ev,
-    output_dir=output_dir,
-    diffraction_order=2,
-    multilayer_bragg_order=1,
-    rough_scan_half_width_deg=5,
-    rough_scan_points=31,
-    rough_fourier_orders=2,
-    rough_x_resolution_nm=1.0,
-    rough_z_resolution_nm=1.0,
-    fine_scan_half_width_deg=2,
-    fine_scan_points=41,
-    fine_fourier_orders=3,
-    fine_x_resolution_nm=0.5,
-    fine_z_resolution_nm=0.5,
-    final_fourier_orders=15,
-    final_x_resolution_nm=0.05,
-    final_z_resolution_nm=0.05,
-    precise_peak_selection_mode="voigt",
-    retry_on_selected_efficiency_zero=True,
-    retry_selected_efficiency_threshold=0.001,
-    max_zero_efficiency_retries=3,
-    max_workers="auto",
-    show_progress=True,
-    live_plot=True,
-    on_error="fail_fast",
-    checkpoint_dir=output_dir / "checkpoints",
-    resume=True,
-    theta_tracking_mode="auto",
-    max_tracking_energy_step_ev=None,
-    backend="numba",
+parser = argparse.ArgumentParser(description="Multilayer theta-search sweep")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
 )
+args = parser.parse_args()
+
+# Guard the executable part: the batch runner spawns worker processes on macOS,
+# and a spawned worker re-imports this file by path. Without the guard each
+# worker re-runs the whole example and recursively spawns more, which fails with
+# BrokenProcessPool before any case completes.
+if __name__ == "__main__":
+    sweep = grax.run_multilayer_theta_search_sweep(
+        solver=args.solver,
+        grating=grating,
+        energies_ev=energies_ev,
+        output_dir=output_dir,
+        diffraction_order=2,
+        multilayer_bragg_order=1,
+        rough_scan_half_width_deg=5,
+        rough_scan_points=31,
+        rough_fourier_orders=2,
+        rough_x_resolution_nm=1.0,
+        rough_z_resolution_nm=1.0,
+        fine_scan_half_width_deg=2,
+        fine_scan_points=41,
+        fine_fourier_orders=3,
+        fine_x_resolution_nm=0.5,
+        fine_z_resolution_nm=0.5,
+        final_fourier_orders=15,
+        final_x_resolution_nm=0.05,
+        final_z_resolution_nm=0.05,
+        precise_peak_selection_mode="voigt",
+        retry_on_selected_efficiency_zero=True,
+        retry_selected_efficiency_threshold=0.001,
+        max_zero_efficiency_retries=3,
+        max_workers="auto",
+        show_progress=True,
+        live_plot=True,
+        on_error="fail_fast",
+        checkpoint_dir=output_dir / f"checkpoints_{args.solver}",
+        resume=True,
+        theta_tracking_mode="auto",
+        max_tracking_energy_step_ev=None,
+        backend="numba",
+    )
 
-logger.info("Sweep completed successfully.")
-print(f"Summary saved to: {sweep.summary_csv_path}")
-print(f"All-order CSV saved to: {sweep.all_orders_csv_path}")
-print(f"Final efficiency plot saved to: {sweep.energy_efficiency_plot_path}")
-print(f"Workflow plot saved to: {sweep.workflow_plot_path}")
-print(f"Total accumulated scan time: {sweep.total_elapsed_seconds:.1f} s")
-if sweep.profile_plot_path is not None:
-    print(f"Profile plot saved to: {sweep.profile_plot_path}")
-if sweep.stack_plot_path is not None:
-    print(f"Stack schematic saved to: {sweep.stack_plot_path}")
-print(f"Per-energy theta scans saved to: {sweep.theta_scan_directory}")
-logger.info("Outputs written under: %s", output_dir)
+    logger.info("Sweep completed successfully.")
+    print(f"Summary saved to: {sweep.summary_csv_path}")
+    print(f"All-order CSV saved to: {sweep.all_orders_csv_path}")
+    print(f"Final efficiency plot saved to: {sweep.energy_efficiency_plot_path}")
+    print(f"Workflow plot saved to: {sweep.workflow_plot_path}")
+    print(f"Total accumulated scan time: {sweep.total_elapsed_seconds:.1f} s")
+    if sweep.profile_plot_path is not None:
+        print(f"Profile plot saved to: {sweep.profile_plot_path}")
+    if sweep.stack_plot_path is not None:
+        print(f"Stack schematic saved to: {sweep.stack_plot_path}")
+    print(f"Per-energy theta scans saved to: {sweep.theta_scan_directory}")
+    logger.info("Outputs written under: %s", output_dir)
diff --git a/examples/simulation/multilayer_theta_search/results/blazed_multilayer_profile.png b/examples/simulation/multilayer_theta_search/results/blazed_multilayer_profile.png
index 3572c5d..4c7abc4 100644
Binary files a/examples/simulation/multilayer_theta_search/results/blazed_multilayer_profile.png and b/examples/simulation/multilayer_theta_search/results/blazed_multilayer_profile.png differ
diff --git a/examples/simulation/multilayer_theta_search/results/checkpoints/metadata.json b/examples/simulation/multilayer_theta_search/results/checkpoints/metadata.json
index 0c895a0..f37ad21 100644
--- a/examples/simulation/multilayer_theta_search/results/checkpoints/metadata.json
+++ b/examples/simulation/multilayer_theta_search/results/checkpoints/metadata.json
@@ -2,12 +2,12 @@
   "created": "2026-05-13T13:58:21.386289",
   "workflow": "multilayer_theta_search",
   "requested_max_workers": "auto",
-  "resolved_max_workers": 30,
+  "resolved_max_workers": 8,
   "theta_tracking_mode": "auto",
   "max_tracking_energy_step_ev": null,
   "resume": true,
-  "current_run_started": "2026-05-13T14:02:32.736951",
-  "last_updated": "2026-05-13T14:43:23.300384",
-  "cumulative_elapsed_seconds": 2659.4856499920006,
-  "last_run_elapsed_seconds": 2450.5634263720003
+  "current_run_started": "2026-08-16T13:30:46.355398",
+  "last_updated": "2026-08-16T13:46:22.261145",
+  "cumulative_elapsed_seconds": 3620.233150117003,
+  "last_run_elapsed_seconds": 935.8722756250027
 }
\ No newline at end of file
diff --git a/examples/simulation/multilayer_theta_search/results/checkpoints/results.jsonl b/examples/simulation/multilayer_theta_search/results/checkpoints/results.jsonl
index 034ed50..bdefe3e 100644
--- a/examples/simulation/multilayer_theta_search/results/checkpoints/results.jsonl
+++ b/examples/simulation/multilayer_theta_search/results/checkpoints/results.jsonl
@@ -549,3 +549,561 @@
 {"case_id": "multilayer-theta-search-00000550", "index": 539, "label": null, "energy_ev": 6000.0, "grazing_angle_deg": 0.3616840081868074, "orders": [-15, -14, -13, -12, -11, -10, -9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], "selected_efficiency": 0.026784342462976382, "selected_diffraction_angle_deg": 2.5775904750011165, "efficiency_all": [1.6099647121073654e-08, 1.0995788521876999e-09, 2.1759266387984386e-08, 6.223980456054115e-08, 1.4806931039935854e-08, 8.876693349809325e-08, 6.367232260862828e-09, 2.675731332089278e-06, 3.2756559849098356e-06, 2.336868577181358e-05, 3.847575482158346e-06, 0.0001726382124602005, 0.001507747304289174, 0.026784342462976382, 0.005037083289911823, 0.6534002399052216, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "diffraction_angle_all": [7.002291981709021, 6.765221767790081, 6.519578160499975, 6.264352660265445, 5.998322260102611, 5.719979565291638, 5.42743059938374, 5.118239909628812, 4.789185379249446, 4.4358486414053, 4.051882189304749, 3.6275728389881152, 3.146642533522936, 2.5775904750011165, 1.8404142896100382, 0.36168400818692703, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "status": "ok", "error_message": null, "case_data": {"workflow": "multilayer_theta_search", "rough_fourier_orders": 2, "fine_fourier_orders": 3, "final_fourier_orders": 15, "rough_x_resolution_nm": 1.0, "rough_z_resolution_nm": 1.0, "fine_x_resolution_nm": 0.5, "fine_z_resolution_nm": 0.5, "final_x_resolution_nm": 0.05, "final_z_resolution_nm": 0.05, "rough_scan_half_width_deg": 0.5294975230401333, "rough_scan_points": 31, "precise_scan_half_width_deg": 0.10589950460802666, "precise_scan_points": 41, "multilayer_bragg_order": 1, "precise_peak_selection_mode": "voigt", "diffraction_order": 2, "roughness_sigma_nm": null, "case_id": "multilayer-theta-search-00000550", "energy_ev": 6000.0, "theta_tracking_center_mode": "bragg", "theta_tracking_auto_classification": "auto_sparse", "theta_tracking_previous_energy_ev": 5880.0, "theta_tracking_previous_grazing_angle_deg": 0.3716393896275164, "theta_tracking_used_previous_theta": false, "theta_tracking_bragg_fallback_triggered": false, "theta_tracking_continuity_rejected": false}, "theta_search_diagnostics": {"estimated_grazing_angle_deg": 1.2876044108943778, "rough_grazing_angles_deg": [0.045847807238314275, 0.10392169640684562, 0.16199558557537697, 0.22006947474390834, 0.27814336391243966, 0.33621725308097106, 0.3942911422495024, 0.45236503141803375, 0.5104389205865651, 0.5685128097550964, 0.6265866989236278, 0.6846605880921591, 0.7427344772606905, 0.8008083664292218, 0.8588822555977532, 0.9169561447662845, 0.9750300339348159, 1.0331039231033472, 1.0911778122718787, 1.1492517014404098, 1.2073255906089413, 1.2653994797774728, 1.3234733689460039, 1.3815472581145354, 1.439621147283067, 1.497695036451598, 1.5557689256201295, 1.613842814788661, 1.671916703957192, 1.7299905931257236, 1.7880644822942546], "rough_efficiencies": [0.00019535572569144886, 0.0005001691553143667, 0.0009811036432700881, 0.0019128147586542114, 0.004204461778790176, 0.01277665358870676, 0.007185328153693776, 0.0021310173943841757, 0.0005029002161105978, 0.0007088144776540958, 0.0004385835021592133, 0.00021732077488532383, 0.00018860363623022296, 0.00011587527223695768, 4.638019336849945e-05, 4.319064332391076e-05, 2.308238471523745e-05, 1.0985719250358396e-05, 4.0554550229347e-06, 1.0219352849924516e-06, 7.490616976730306e-07, 1.626589906622212e-07, 1.0882463219912776e-06, 2.4084440115869707e-06, 5.139527132731023e-06, 1.0102292376569897e-05, 1.5712165303718086e-06, 1.7502958155629918e-06, 7.837519465885808e-06, 2.0650253580895462e-05, 2.457539795836725e-05], "precise_grazing_angles_deg": [0.2303177484729444, 0.23561272370334574, 0.24090769893374706, 0.2462026741641484, 0.2514976493945497, 0.25679262462495106, 0.2620875998553524, 0.26738257508575375, 0.27267755031615504, 0.2779725255465564, 0.2832675007769577, 0.28856247600735907, 0.2938574512377604, 0.2991524264681617, 0.30444740169856305, 0.3097423769289644, 0.31503735215936574, 0.320332327389767, 0.32562730262016837, 0.3309222778505697, 0.33621725308097106, 0.3415122283113724, 0.34680720354177375, 0.35210217877217503, 0.3573971540025764, 0.3626921292329777, 0.367987104463379, 0.37328207969378036, 0.3785770549241817, 0.38387203015458304, 0.3891670053849844, 0.39446198061538573, 0.3997569558457871, 0.4050519310761884, 0.4103469063065897, 0.41564188153699105, 0.42093685676739234, 0.4262318319977937, 0.43152680722819503, 0.4368217824585964, 0.4421167576889977], "precise_efficiencies": [0.0024534327988560817, 0.0026225381005619253, 0.0028067802277904844, 0.003008032439703123, 0.0032284651757052496, 0.0034706050346789293, 0.0037374079149844128, 0.004032350268832212, 0.004359543639898378, 0.0047238791999342925, 0.005131210863426664, 0.0055885871598128295, 0.006104540268083298, 0.006689429218182118, 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diff --git a/examples/simulation/multilayer_theta_search/results/checkpoints_rcwa/metadata.json b/examples/simulation/multilayer_theta_search/results/checkpoints_rcwa/metadata.json
new file mode 100644
index 0000000..a8301f4
--- /dev/null
+++ b/examples/simulation/multilayer_theta_search/results/checkpoints_rcwa/metadata.json
@@ -0,0 +1,13 @@
+{
+  "created": "2026-08-17T10:24:56.463314",
+  "workflow": "multilayer_theta_search",
+  "requested_max_workers": "auto",
+  "resolved_max_workers": 8,
+  "theta_tracking_mode": "auto",
+  "max_tracking_energy_step_ev": null,
+  "resume": true,
+  "current_run_started": "2026-08-17T10:24:56.463314",
+  "last_updated": "2026-08-17T10:38:44.887547",
+  "cumulative_elapsed_seconds": 828.4161603329994,
+  "last_run_elapsed_seconds": 828.4161603329994
+}
\ No newline at end of file
diff --git a/examples/simulation/multilayer_theta_search/results/checkpoints_rcwa/results.jsonl b/examples/simulation/multilayer_theta_search/results/checkpoints_rcwa/results.jsonl
new file mode 100644
index 0000000..5b41ca2
--- /dev/null
+++ b/examples/simulation/multilayer_theta_search/results/checkpoints_rcwa/results.jsonl
@@ -0,0 +1,551 @@
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diff --git a/examples/simulation/multilayer_theta_search/results/multilayer_stack_schematic.png b/examples/simulation/multilayer_theta_search/results/multilayer_stack_schematic.png
index e5c6ceb..17fdd24 100644
Binary files a/examples/simulation/multilayer_theta_search/results/multilayer_stack_schematic.png and b/examples/simulation/multilayer_theta_search/results/multilayer_stack_schematic.png differ
diff --git a/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_all_orders.csv b/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_all_orders.csv
index e306588..c3a504c 100644
--- a/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_all_orders.csv
+++ b/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_all_orders.csv
@@ -1,17082 +1,17082 @@
 energy_ev,selected_grazing_angle_deg,order,efficiency,diffraction_angle_deg,retry_triggered,retry_attempts,retry_status,selected_efficiency_is_exact_zero,selected_efficiency_below_retry_threshold,theta_tracking_center_mode,theta_tracking_auto_classification,theta_tracking_previous_energy_ev,theta_tracking_previous_grazing_angle_deg,theta_tracking_used_previous_theta,theta_tracking_bragg_fallback_triggered,theta_tracking_continuity_rejected,precise_peak_selection_mode_requested,precise_peak_selection_mode_used,precise_peak_fit_fallback_used,precise_peak_fitted_center_deg,precise_peak_fitted_fwhm_deg
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diff --git a/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_energy_vs_efficiency.png b/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_energy_vs_efficiency.png
index 5c56fdb..3fb5af9 100644
Binary files a/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_energy_vs_efficiency.png and b/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_energy_vs_efficiency.png differ
diff --git a/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_summary.csv b/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_summary.csv
index f098a20..34c17db 100644
--- a/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_summary.csv
+++ b/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_summary.csv
@@ -1,552 +1,552 @@
 energy_ev,selected_grazing_angle_deg,selected_efficiency,precise_fwhm_deg,retry_triggered,retry_attempts,retry_status,selected_efficiency_is_exact_zero,selected_efficiency_below_retry_threshold,theta_tracking_center_mode,theta_tracking_auto_classification,theta_tracking_previous_energy_ev,theta_tracking_previous_grazing_angle_deg,theta_tracking_used_previous_theta,theta_tracking_bragg_fallback_triggered,theta_tracking_continuity_rejected,precise_peak_selection_mode_requested,precise_peak_selection_mode_used,precise_peak_fit_fallback_used,precise_peak_fitted_center_deg,precise_peak_fitted_fwhm_deg
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diff --git a/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_workflow.png b/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_workflow.png
index 9993f9b..f65e971 100644
Binary files a/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_workflow.png and b/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_workflow.png differ
diff --git a/examples/simulation/neviere_solver/neviere_solver.py b/examples/simulation/neviere_solver/neviere_solver.py
new file mode 100644
index 0000000..287fbe8
--- /dev/null
+++ b/examples/simulation/neviere_solver/neviere_solver.py
@@ -0,0 +1,158 @@
+"""Compare the RCWA and Nevière differential-method solvers on one grating.
+
+Runs the same laminar grating through both solvers over a short energy sweep,
+writes the per-order efficiencies for each, and plots them together with the
+per-energy difference. Also demonstrates continuous permittivity sampling, which
+drops the staircase approximation both solvers otherwise share.
+"""
+
+from __future__ import annotations
+
+import dataclasses
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+import grax
+
+if __name__ == "__main__":
+    output_dir = Path(__file__).resolve().parent / "results"
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    grating = grax.LaminarGrating(
+        period_lpermm=400,
+        width_to_period_ratio=0.67,
+        depth_nm=14.9,
+        left_wall_angle_deg=15.0,
+        right_wall_angle_deg=15.0,
+        substrate_material="Si",
+        layer_material="Pt",
+        layer_thickness_nm=28.77,
+        x_resolution_nm=1.0,
+        z_resolution_nm=0.5,
+    )
+
+    energies_ev = np.arange(50.0, 600.1, 5.0)
+    grazing_angle_deg = 4.0
+    diffraction_order = 1
+    fourier_orders = 12
+
+    # 1. One point through each solver. Only the `solver` argument changes.
+    single_common = dict(
+        grating=grating,
+        energy_ev=float(energies_ev[len(energies_ev) // 2]),
+        grazing_angle_deg=grazing_angle_deg,
+        diffraction_order=diffraction_order,
+        fourier_orders=fourier_orders,
+        polarization="p",
+    )
+    rcwa_single = grax.run_simulation(**single_common, solver="rcwa")
+    neviere_single = grax.run_simulation(**single_common, solver="neviere")
+
+    print(f"At {single_common['energy_ev']:.0f} eV, order {diffraction_order}:")
+    print(f"  rcwa     : {rcwa_single.selected_efficiency:.12f}")
+    print(f"  neviere  : {neviere_single.selected_efficiency:.12f}")
+    print(
+        "  difference: "
+        f"{abs(rcwa_single.selected_efficiency - neviere_single.selected_efficiency):.3e}"
+    )
+    print(f"  result.solver reports: {rcwa_single.solver!r} and {neviere_single.solver!r}")
+
+    # 2. Tightening the integration drives the residual towards zero, which shows the
+    #    difference is Runge-Kutta truncation error rather than a modelling gap.
+    tight = grax.run_simulation(
+        **single_common,
+        solver="neviere",
+        solver_options=grax.NeviereOptions(step_phase=0.005),
+    )
+    print(
+        "  difference with step_phase=0.005: "
+        f"{abs(rcwa_single.selected_efficiency - tight.selected_efficiency):.3e}"
+    )
+
+    # 3. Continuous permittivity sampling reads the true profile instead of the
+    #    z-sliced staircase, so its answer does not depend on z_resolution_nm. It
+    #    therefore differs from the two runs above, which share that staircase: a
+    #    much more finely sliced staircase run shows which of them is converged.
+    continuous = grax.run_simulation(
+        **single_common,
+        solver="neviere",
+        solver_options=grax.NeviereOptions(z_sampling="continuous"),
+    )
+    fine_staircase = grax.run_simulation(
+        **{**single_common, "grating": dataclasses.replace(grating, z_resolution_nm=0.01)},
+        solver="rcwa",
+    )
+    print(f"\nStaircase at z_resolution_nm={grating.z_resolution_nm}: "
+          f"{rcwa_single.selected_efficiency:.12f}")
+    print(f"Staircase at z_resolution_nm=0.01     : {fine_staircase.selected_efficiency:.12f}")
+    print(f"Continuous sampling (no staircase)    : {continuous.selected_efficiency:.12f}")
+    print(
+        "  continuous vs converged staircase: "
+        f"{abs(continuous.selected_efficiency - fine_staircase.selected_efficiency):.3e}"
+    )
+
+    # 4. A short sweep through each solver, via the batch runner.
+    efficiencies: dict[str, np.ndarray] = {}
+    for solver in ("rcwa", "neviere"):
+        runner = grax.BatchSimulationRunner(
+            diffraction_order=diffraction_order,
+            fourier_orders=fourier_orders,
+            solver=solver,
+            on_error="fail_fast",
+            max_workers="auto",
+            live_plot=True,
+            live_plot_x_key="energy_ev",
+        )
+        cases = grax.fixed_angle_cases(
+            grating=grating,
+            energies_ev=energies_ev,
+            grazing_angle_deg=grazing_angle_deg,
+            polarization="p",
+        )
+        results = [case for case in runner.run_cases(cases) if case.status == "ok"]
+        efficiencies[solver] = np.asarray(
+            [case.selected_efficiency for case in results], dtype=float
+        )
+        grax.write_all_orders_csv(results, output_dir / f"neviere_solver_{solver}.csv")
+
+    figure, axes = plt.subplots(
+        2,
+        1,
+        figsize=(10, 7),
+        sharex=True,
+        gridspec_kw={"height_ratios": [2.2, 1.0]},
+    )
+    efficiency_axis, difference_axis = axes
+    efficiency_axis.plot(energies_ev, efficiencies["rcwa"], "-o", markersize=3.0, label="RCWA (modal)")
+    efficiency_axis.plot(
+        energies_ev,
+        efficiencies["neviere"],
+        "--s",
+        markersize=3.0,
+        label="Nevière (differential)",
+    )
+    efficiency_axis.set_ylabel(f"Efficiency (order {diffraction_order})")
+    efficiency_axis.set_title("Laminar 400 l/mm at 4 deg grazing: RCWA vs Nevière")
+    efficiency_axis.grid(True, alpha=0.3)
+    efficiency_axis.legend(loc="best")
+
+    difference_axis.semilogy(
+        energies_ev,
+        np.abs(efficiencies["rcwa"] - efficiencies["neviere"]),
+        "-",
+        color="tab:red",
+    )
+    difference_axis.set_xlabel("Photon energy (eV)")
+    difference_axis.set_ylabel("|RCWA - Nevière|")
+    difference_axis.grid(True, alpha=0.3, which="both")
+
+    figure.tight_layout()
+    plot_path = output_dir / "neviere_solver_comparison.png"
+    figure.savefig(plot_path, dpi=150, bbox_inches="tight")
+    plt.close(figure)
+
+    print(f"\nMaximum sweep difference: {np.max(np.abs(efficiencies['rcwa'] - efficiencies['neviere'])):.3e}")
+    print(f"Comparison plot saved to: {plot_path}")
+    print(f"Per-solver CSVs saved to: {output_dir}")
diff --git a/examples/simulation/neviere_solver/results/neviere_solver_comparison.png b/examples/simulation/neviere_solver/results/neviere_solver_comparison.png
new file mode 100644
index 0000000..db621fe
Binary files /dev/null and b/examples/simulation/neviere_solver/results/neviere_solver_comparison.png differ
diff --git a/examples/simulation/neviere_solver/results/neviere_solver_neviere.csv b/examples/simulation/neviere_solver/results/neviere_solver_neviere.csv
new file mode 100644
index 0000000..5e3bfe9
--- /dev/null
+++ b/examples/simulation/neviere_solver/results/neviere_solver_neviere.csv
@@ -0,0 +1,276 @@
+case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
+fixed-00000000,100.0,4.0,-12,0.0038453187634065874,20.272780035826898
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+fixed-00000000,100.0,4.0,-7,0.0032608253048751704,15.666531340439832
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+fixed-00000000,100.0,4.0,-4,0.010519897911180017,12.115293466158093
+fixed-00000000,100.0,4.0,-3,0.006010649554815903,10.677246924869166
+fixed-00000000,100.0,4.0,-2,0.01415678362441888,9.015622340555609
+fixed-00000000,100.0,4.0,-1,0.12639057427038858,6.972349028947534
+fixed-00000000,100.0,4.0,0,0.6605290066856145,4.000000000000043
+fixed-00000000,100.0,4.0,1,0.0,0.0
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diff --git a/examples/simulation/neviere_solver/results/neviere_solver_rcwa.csv b/examples/simulation/neviere_solver/results/neviere_solver_rcwa.csv
new file mode 100644
index 0000000..7804ae7
--- /dev/null
+++ b/examples/simulation/neviere_solver/results/neviere_solver_rcwa.csv
@@ -0,0 +1,276 @@
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diff --git a/examples/simulation/parameter_study/parameter_study.py b/examples/simulation/parameter_study/parameter_study.py
index f1904a2..8588652 100644
--- a/examples/simulation/parameter_study/parameter_study.py
+++ b/examples/simulation/parameter_study/parameter_study.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import argparse
 from pathlib import Path
 
 import grax
@@ -26,7 +27,18 @@
 x_resolution_values = grax.get_default_parameter_study_ranges()[1]
 z_resolution_values = grax.get_default_parameter_study_ranges()[2]
 
+parser = argparse.ArgumentParser(description="Convergence parameter study")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
+)
+args = parser.parse_args()
+
 study = grax.run_parameter_study(
+    solver=args.solver,
     grating=grating,
     energies_ev=energies_ev,
     grazing_angle_deg=grazing_angle_deg,
@@ -40,7 +52,7 @@
     show_progress=True,
 )
 
-plot_path = output_dir / "parameter_study_grid.png"
+plot_path = output_dir / f"parameter_study_grid_{args.solver}.png"
 grax.plot_parameter_study(
     study,
     output_filename=plot_path,
diff --git a/examples/simulation/parameter_study/results/parameter_study_fourier_orders_E100.0eV.csv b/examples/simulation/parameter_study/results/parameter_study_fourier_orders_E100.0eV.csv
index f75246b..d1945e6 100644
--- a/examples/simulation/parameter_study/results/parameter_study_fourier_orders_E100.0eV.csv
+++ b/examples/simulation/parameter_study/results/parameter_study_fourier_orders_E100.0eV.csv
@@ -1,12 +1,12 @@
 parameter,value,efficiency,error,error_message,energy_ev,grazing_angle_deg
-fourier_orders,5,0.05046435651040239,False,,100.0,1.5
-fourier_orders,7,0.05142250492569445,False,,100.0,1.5
-fourier_orders,9,0.05175267096907875,False,,100.0,1.5
-fourier_orders,11,0.051910270157257375,False,,100.0,1.5
-fourier_orders,13,0.05203352809133029,False,,100.0,1.5
-fourier_orders,15,0.052132647590110645,False,,100.0,1.5
-fourier_orders,17,0.052205497809560616,False,,100.0,1.5
-fourier_orders,19,0.05225518646480622,False,,100.0,1.5
-fourier_orders,21,0.05228805954081444,False,,100.0,1.5
-fourier_orders,23,0.052310109925101204,False,,100.0,1.5
-fourier_orders,25,0.05232559538861387,False,,100.0,1.5
+fourier_orders,5,0.04887917038527679,False,,100.0,1.5
+fourier_orders,7,0.049776867596570365,False,,100.0,1.5
+fourier_orders,9,0.050097833832407394,False,,100.0,1.5
+fourier_orders,11,0.05026392044954374,False,,100.0,1.5
+fourier_orders,13,0.05039038068729162,False,,100.0,1.5
+fourier_orders,15,0.050484880485162115,False,,100.0,1.5
+fourier_orders,17,0.050549962908922344,False,,100.0,1.5
+fourier_orders,19,0.050592694205691804,False,,100.0,1.5
+fourier_orders,21,0.05062064722266248,False,,100.0,1.5
+fourier_orders,23,0.050639378956395475,False,,100.0,1.5
+fourier_orders,25,0.050652628537678,False,,100.0,1.5
diff --git a/examples/simulation/parameter_study/results/parameter_study_fourier_orders_E2000.0eV.csv b/examples/simulation/parameter_study/results/parameter_study_fourier_orders_E2000.0eV.csv
index d5177e4..6a3b422 100644
--- a/examples/simulation/parameter_study/results/parameter_study_fourier_orders_E2000.0eV.csv
+++ b/examples/simulation/parameter_study/results/parameter_study_fourier_orders_E2000.0eV.csv
@@ -1,12 +1,12 @@
 parameter,value,efficiency,error,error_message,energy_ev,grazing_angle_deg
-fourier_orders,5,0.11289163661917219,False,,2000.0,1.5
-fourier_orders,7,0.11285278798810235,False,,2000.0,1.5
-fourier_orders,9,0.11284050684700314,False,,2000.0,1.5
-fourier_orders,11,0.11284458652677559,False,,2000.0,1.5
-fourier_orders,13,0.11284439246080549,False,,2000.0,1.5
-fourier_orders,15,0.11284229375449219,False,,2000.0,1.5
-fourier_orders,17,0.11284124876447543,False,,2000.0,1.5
-fourier_orders,19,0.11284138516504597,False,,2000.0,1.5
-fourier_orders,21,0.11284140699631136,False,,2000.0,1.5
-fourier_orders,23,0.1128409661836062,False,,2000.0,1.5
-fourier_orders,25,0.11284052500591464,False,,2000.0,1.5
+fourier_orders,5,0.11275393241386837,False,,2000.0,1.5
+fourier_orders,7,0.11271366302068485,False,,2000.0,1.5
+fourier_orders,9,0.11270047121991043,False,,2000.0,1.5
+fourier_orders,11,0.11270386943853263,False,,2000.0,1.5
+fourier_orders,13,0.11270322908546247,False,,2000.0,1.5
+fourier_orders,15,0.11270081916614491,False,,2000.0,1.5
+fourier_orders,17,0.11269952885324978,False,,2000.0,1.5
+fourier_orders,19,0.11269945796295498,False,,2000.0,1.5
+fourier_orders,21,0.11269931429811478,False,,2000.0,1.5
+fourier_orders,23,0.11269874429300046,False,,2000.0,1.5
+fourier_orders,25,0.112698194865141,False,,2000.0,1.5
diff --git a/examples/simulation/parameter_study/results/parameter_study_fourier_orders_E600.0eV.csv b/examples/simulation/parameter_study/results/parameter_study_fourier_orders_E600.0eV.csv
index 0dd3f65..08f7e5c 100644
--- a/examples/simulation/parameter_study/results/parameter_study_fourier_orders_E600.0eV.csv
+++ b/examples/simulation/parameter_study/results/parameter_study_fourier_orders_E600.0eV.csv
@@ -1,12 +1,12 @@
 parameter,value,efficiency,error,error_message,energy_ev,grazing_angle_deg
-fourier_orders,5,0.2524676501272089,False,,600.0,1.5
-fourier_orders,7,0.2530816072105681,False,,600.0,1.5
-fourier_orders,9,0.25316352428248584,False,,600.0,1.5
-fourier_orders,11,0.253205472926002,False,,600.0,1.5
-fourier_orders,13,0.253220240591596,False,,600.0,1.5
-fourier_orders,15,0.2532268065791318,False,,600.0,1.5
-fourier_orders,17,0.25323239623154226,False,,600.0,1.5
-fourier_orders,19,0.2532371913880235,False,,600.0,1.5
-fourier_orders,21,0.2532409167141548,False,,600.0,1.5
-fourier_orders,23,0.25324369549081444,False,,600.0,1.5
-fourier_orders,25,0.25324575853201436,False,,600.0,1.5
+fourier_orders,5,0.25074467439068393,False,,600.0,1.5
+fourier_orders,7,0.2513050180650042,False,,600.0,1.5
+fourier_orders,9,0.25136173578308746,False,,600.0,1.5
+fourier_orders,11,0.2513871880903217,False,,600.0,1.5
+fourier_orders,13,0.2513905947645017,False,,600.0,1.5
+fourier_orders,15,0.25138881718892736,False,,600.0,1.5
+fourier_orders,17,0.2513878038788341,False,,600.0,1.5
+fourier_orders,19,0.2513872271532639,False,,600.0,1.5
+fourier_orders,21,0.25138655547267247,False,,600.0,1.5
+fourier_orders,23,0.2513856835466919,False,,600.0,1.5
+fourier_orders,25,0.2513846696379768,False,,600.0,1.5
diff --git a/examples/simulation/parameter_study/results/parameter_study_grid.png b/examples/simulation/parameter_study/results/parameter_study_grid.png
deleted file mode 100644
index 8a04a2e..0000000
Binary files a/examples/simulation/parameter_study/results/parameter_study_grid.png and /dev/null differ
diff --git a/examples/simulation/parameter_study/results/parameter_study_grid_neviere.png b/examples/simulation/parameter_study/results/parameter_study_grid_neviere.png
new file mode 100644
index 0000000..74b5857
Binary files /dev/null and b/examples/simulation/parameter_study/results/parameter_study_grid_neviere.png differ
diff --git a/examples/simulation/parameter_study/results/parameter_study_grid_rcwa.png b/examples/simulation/parameter_study/results/parameter_study_grid_rcwa.png
new file mode 100644
index 0000000..8e003cb
Binary files /dev/null and b/examples/simulation/parameter_study/results/parameter_study_grid_rcwa.png differ
diff --git a/examples/simulation/parameter_study/results/parameter_study_profile.png b/examples/simulation/parameter_study/results/parameter_study_profile.png
index bf9daa5..38b32f7 100644
Binary files a/examples/simulation/parameter_study/results/parameter_study_profile.png and b/examples/simulation/parameter_study/results/parameter_study_profile.png differ
diff --git a/examples/simulation/parameter_study/results/parameter_study_x_resolution_nm_E100.0eV.csv b/examples/simulation/parameter_study/results/parameter_study_x_resolution_nm_E100.0eV.csv
index a662b5d..9d839b0 100644
--- a/examples/simulation/parameter_study/results/parameter_study_x_resolution_nm_E100.0eV.csv
+++ b/examples/simulation/parameter_study/results/parameter_study_x_resolution_nm_E100.0eV.csv
@@ -1,11 +1,11 @@
 parameter,value,efficiency,error,error_message,energy_ev,grazing_angle_deg
-x_resolution_nm,10.0,0.05293221447087048,False,,100.0,1.5
-x_resolution_nm,5.99484250318941,0.052680026252913695,False,,100.0,1.5
-x_resolution_nm,3.5938136638046276,0.05252220099801764,False,,100.0,1.5
-x_resolution_nm,2.154434690031884,0.05243031566924173,False,,100.0,1.5
-x_resolution_nm,1.291549665014884,0.05237635449969325,False,,100.0,1.5
-x_resolution_nm,0.774263682681127,0.052340787457663414,False,,100.0,1.5
-x_resolution_nm,0.464158883361278,0.052322490690757735,False,,100.0,1.5
-x_resolution_nm,0.2782559402207126,0.05231074425032537,False,,100.0,1.5
-x_resolution_nm,0.1668100537200059,0.052303465667117105,False,,100.0,1.5
-x_resolution_nm,0.1,0.05229953814759874,False,,100.0,1.5
+x_resolution_nm,10.0,0.05124367429813818,False,,100.0,1.5
+x_resolution_nm,5.99484250318941,0.050993581159417656,False,,100.0,1.5
+x_resolution_nm,3.5938136638046276,0.05084311781537553,False,,100.0,1.5
+x_resolution_nm,2.154434690031884,0.050754363664484645,False,,100.0,1.5
+x_resolution_nm,1.291549665014884,0.05070147847776109,False,,100.0,1.5
+x_resolution_nm,0.774263682681127,0.050667610033008376,False,,100.0,1.5
+x_resolution_nm,0.464158883361278,0.0506498774144599,False,,100.0,1.5
+x_resolution_nm,0.2782559402207126,0.05063838581842061,False,,100.0,1.5
+x_resolution_nm,0.1668100537200059,0.050631305453706164,False,,100.0,1.5
+x_resolution_nm,0.1,0.05062748547519894,False,,100.0,1.5
diff --git a/examples/simulation/parameter_study/results/parameter_study_x_resolution_nm_E2000.0eV.csv b/examples/simulation/parameter_study/results/parameter_study_x_resolution_nm_E2000.0eV.csv
index 8dab807..37fee51 100644
--- a/examples/simulation/parameter_study/results/parameter_study_x_resolution_nm_E2000.0eV.csv
+++ b/examples/simulation/parameter_study/results/parameter_study_x_resolution_nm_E2000.0eV.csv
@@ -1,11 +1,11 @@
 parameter,value,efficiency,error,error_message,energy_ev,grazing_angle_deg
-x_resolution_nm,10.0,0.11074938262388681,False,,2000.0,1.5
-x_resolution_nm,5.99484250318941,0.1116229473628715,False,,2000.0,1.5
-x_resolution_nm,3.5938136638046276,0.112166438285863,False,,2000.0,1.5
-x_resolution_nm,2.154434690031884,0.1124819441887601,False,,2000.0,1.5
-x_resolution_nm,1.291549665014884,0.11267160655107984,False,,2000.0,1.5
-x_resolution_nm,0.774263682681127,0.11278581928244837,False,,2000.0,1.5
-x_resolution_nm,0.464158883361278,0.11285215745331967,False,,2000.0,1.5
-x_resolution_nm,0.2782559402207126,0.1128902005438266,False,,2000.0,1.5
-x_resolution_nm,0.1668100537200059,0.11291393061678459,False,,2000.0,1.5
-x_resolution_nm,0.1,0.11292727832702157,False,,2000.0,1.5
+x_resolution_nm,10.0,0.11061114443403895,False,,2000.0,1.5
+x_resolution_nm,5.99484250318941,0.11148307332284302,False,,2000.0,1.5
+x_resolution_nm,3.5938136638046276,0.11202543847187875,False,,2000.0,1.5
+x_resolution_nm,2.154434690031884,0.11234032565965588,False,,2000.0,1.5
+x_resolution_nm,1.291549665014884,0.11252962787301837,False,,2000.0,1.5
+x_resolution_nm,0.774263682681127,0.11264358814509262,False,,2000.0,1.5
+x_resolution_nm,0.464158883361278,0.11270979492528864,False,,2000.0,1.5
+x_resolution_nm,0.2782559402207126,0.11274775900245292,False,,2000.0,1.5
+x_resolution_nm,0.1668100537200059,0.11277144249010537,False,,2000.0,1.5
+x_resolution_nm,0.1,0.11278476642781668,False,,2000.0,1.5
diff --git a/examples/simulation/parameter_study/results/parameter_study_x_resolution_nm_E600.0eV.csv b/examples/simulation/parameter_study/results/parameter_study_x_resolution_nm_E600.0eV.csv
index 497938d..0e4e87b 100644
--- a/examples/simulation/parameter_study/results/parameter_study_x_resolution_nm_E600.0eV.csv
+++ b/examples/simulation/parameter_study/results/parameter_study_x_resolution_nm_E600.0eV.csv
@@ -1,11 +1,11 @@
 parameter,value,efficiency,error,error_message,energy_ev,grazing_angle_deg
-x_resolution_nm,10.0,0.2534385075683811,False,,600.0,1.5
-x_resolution_nm,5.99484250318941,0.2533799337470298,False,,600.0,1.5
-x_resolution_nm,3.5938136638046276,0.2533167265786756,False,,600.0,1.5
-x_resolution_nm,2.154434690031884,0.25328573457757336,False,,600.0,1.5
-x_resolution_nm,1.291549665014884,0.25327111640436906,False,,600.0,1.5
-x_resolution_nm,0.774263682681127,0.25324985029987174,False,,600.0,1.5
-x_resolution_nm,0.464158883361278,0.25324239686212346,False,,600.0,1.5
-x_resolution_nm,0.2782559402207126,0.253238091458944,False,,600.0,1.5
-x_resolution_nm,0.1668100537200059,0.25323427325304365,False,,600.0,1.5
-x_resolution_nm,0.1,0.25323376951684967,False,,600.0,1.5
+x_resolution_nm,10.0,0.2515790412536782,False,,600.0,1.5
+x_resolution_nm,5.99484250318941,0.25151975345020144,False,,600.0,1.5
+x_resolution_nm,3.5938136638046276,0.25145611837723636,False,,600.0,1.5
+x_resolution_nm,2.154434690031884,0.25142491816896856,False,,600.0,1.5
+x_resolution_nm,1.291549665014884,0.25141009940495357,False,,600.0,1.5
+x_resolution_nm,0.774263682681127,0.2513888076848604,False,,600.0,1.5
+x_resolution_nm,0.464158883361278,0.2513813227711709,False,,600.0,1.5
+x_resolution_nm,0.2782559402207126,0.25137698438164163,False,,600.0,1.5
+x_resolution_nm,0.1668100537200059,0.2513731596951779,False,,600.0,1.5
+x_resolution_nm,0.1,0.25137264018062183,False,,600.0,1.5
diff --git a/examples/simulation/parameter_study/results/parameter_study_z_resolution_nm_E100.0eV.csv b/examples/simulation/parameter_study/results/parameter_study_z_resolution_nm_E100.0eV.csv
index 75d4241..da9ffb8 100644
--- a/examples/simulation/parameter_study/results/parameter_study_z_resolution_nm_E100.0eV.csv
+++ b/examples/simulation/parameter_study/results/parameter_study_z_resolution_nm_E100.0eV.csv
@@ -1,11 +1,11 @@
 parameter,value,efficiency,error,error_message,energy_ev,grazing_angle_deg
-z_resolution_nm,10.0,0.06169138704485326,False,,100.0,1.5
-z_resolution_nm,5.99484250318941,0.04641140754543338,False,,100.0,1.5
-z_resolution_nm,3.5938136638046276,0.05355520059692163,False,,100.0,1.5
-z_resolution_nm,2.154434690031884,0.050670587428141685,False,,100.0,1.5
-z_resolution_nm,1.291549665014884,0.05203174961544107,False,,100.0,1.5
-z_resolution_nm,0.774263682681127,0.05181019266560314,False,,100.0,1.5
-z_resolution_nm,0.464158883361278,0.05199379587258169,False,,100.0,1.5
-z_resolution_nm,0.2782559402207126,0.052251525129415985,False,,100.0,1.5
-z_resolution_nm,0.1668100537200059,0.05247871475103445,False,,100.0,1.5
-z_resolution_nm,0.1,0.05232559538861387,False,,100.0,1.5
+z_resolution_nm,10.0,0.059948851425215346,False,,100.0,1.5
+z_resolution_nm,5.99484250318941,0.04499381619880162,False,,100.0,1.5
+z_resolution_nm,3.5938136638046276,0.05190717345380884,False,,100.0,1.5
+z_resolution_nm,2.154434690031884,0.0491306675575201,False,,100.0,1.5
+z_resolution_nm,1.291549665014884,0.05036800798380152,False,,100.0,1.5
+z_resolution_nm,0.774263682681127,0.05014700296779176,False,,100.0,1.5
+z_resolution_nm,0.464158883361278,0.050330365015679675,False,,100.0,1.5
+z_resolution_nm,0.2782559402207126,0.05058246298750819,False,,100.0,1.5
+z_resolution_nm,0.1668100537200059,0.0508017503216396,False,,100.0,1.5
+z_resolution_nm,0.1,0.050652628537678,False,,100.0,1.5
diff --git a/examples/simulation/parameter_study/results/parameter_study_z_resolution_nm_E2000.0eV.csv b/examples/simulation/parameter_study/results/parameter_study_z_resolution_nm_E2000.0eV.csv
index f759511..e549732 100644
--- a/examples/simulation/parameter_study/results/parameter_study_z_resolution_nm_E2000.0eV.csv
+++ b/examples/simulation/parameter_study/results/parameter_study_z_resolution_nm_E2000.0eV.csv
@@ -1,11 +1,11 @@
 parameter,value,efficiency,error,error_message,energy_ev,grazing_angle_deg
-z_resolution_nm,10.0,0.08465353942955033,False,,2000.0,1.5
-z_resolution_nm,5.99484250318941,0.10931981364729387,False,,2000.0,1.5
-z_resolution_nm,3.5938136638046276,0.1022056434616333,False,,2000.0,1.5
-z_resolution_nm,2.154434690031884,0.11595006214202717,False,,2000.0,1.5
-z_resolution_nm,1.291549665014884,0.11229804434060826,False,,2000.0,1.5
-z_resolution_nm,0.774263682681127,0.11441392615348282,False,,2000.0,1.5
-z_resolution_nm,0.464158883361278,0.11387335565516235,False,,2000.0,1.5
-z_resolution_nm,0.2782559402207126,0.11306055724616385,False,,2000.0,1.5
-z_resolution_nm,0.1668100537200059,0.11232289623722713,False,,2000.0,1.5
-z_resolution_nm,0.1,0.11284052500591464,False,,2000.0,1.5
+z_resolution_nm,10.0,0.08452164774543548,False,,2000.0,1.5
+z_resolution_nm,5.99484250318941,0.10917153922938747,False,,2000.0,1.5
+z_resolution_nm,3.5938136638046276,0.10208791705034008,False,,2000.0,1.5
+z_resolution_nm,2.154434690031884,0.11579973183557836,False,,2000.0,1.5
+z_resolution_nm,1.291549665014884,0.11215622682677176,False,,2000.0,1.5
+z_resolution_nm,0.774263682681127,0.11426804967838346,False,,2000.0,1.5
+z_resolution_nm,0.464158883361278,0.11372861802084239,False,,2000.0,1.5
+z_resolution_nm,0.2782559402207126,0.11291764704944102,False,,2000.0,1.5
+z_resolution_nm,0.1668100537200059,0.11218150205497324,False,,2000.0,1.5
+z_resolution_nm,0.1,0.112698194865141,False,,2000.0,1.5
diff --git a/examples/simulation/parameter_study/results/parameter_study_z_resolution_nm_E600.0eV.csv b/examples/simulation/parameter_study/results/parameter_study_z_resolution_nm_E600.0eV.csv
index 961b2bb..180bd8a 100644
--- a/examples/simulation/parameter_study/results/parameter_study_z_resolution_nm_E600.0eV.csv
+++ b/examples/simulation/parameter_study/results/parameter_study_z_resolution_nm_E600.0eV.csv
@@ -1,11 +1,11 @@
 parameter,value,efficiency,error,error_message,energy_ev,grazing_angle_deg
-z_resolution_nm,10.0,0.16387367568471714,False,,600.0,1.5
-z_resolution_nm,5.99484250318941,0.20703709575711204,False,,600.0,1.5
-z_resolution_nm,3.5938136638046276,0.23943462369368482,False,,600.0,1.5
-z_resolution_nm,2.154434690031884,0.24630867978223417,False,,600.0,1.5
-z_resolution_nm,1.291549665014884,0.2509291374120844,False,,600.0,1.5
-z_resolution_nm,0.774263682681127,0.25236693682281214,False,,600.0,1.5
-z_resolution_nm,0.464158883361278,0.252834397981553,False,,600.0,1.5
-z_resolution_nm,0.2782559402207126,0.25311679314917745,False,,600.0,1.5
-z_resolution_nm,0.1668100537200059,0.2532811838181878,False,,600.0,1.5
-z_resolution_nm,0.1,0.25324575853201436,False,,600.0,1.5
+z_resolution_nm,10.0,0.1629909664294295,False,,600.0,1.5
+z_resolution_nm,5.99484250318941,0.20561433373648946,False,,600.0,1.5
+z_resolution_nm,3.5938136638046276,0.23777804263657037,False,,600.0,1.5
+z_resolution_nm,2.154434690031884,0.2445508030306056,False,,600.0,1.5
+z_resolution_nm,1.291549665014884,0.24910723906796586,False,,600.0,1.5
+z_resolution_nm,0.774263682681127,0.2505075804466383,False,,600.0,1.5
+z_resolution_nm,0.464158883361278,0.2509749997751312,False,,600.0,1.5
+z_resolution_nm,0.2782559402207126,0.2512563472856678,False,,600.0,1.5
+z_resolution_nm,0.1668100537200059,0.2514206116291102,False,,600.0,1.5
+z_resolution_nm,0.1,0.2513846696379768,False,,600.0,1.5
diff --git a/examples/simulation/run_all.sh b/examples/simulation/run_all.sh
new file mode 100755
index 0000000..853b744
--- /dev/null
+++ b/examples/simulation/run_all.sh
@@ -0,0 +1,42 @@
+#!/usr/bin/env bash
+# Run every standalone simulation example and its dedicated comparison plots.
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+PYTHON_BIN="${PYTHON_BIN:-python}"
+
+run_example() {
+    local relative_path="$1"
+    echo "==> Running ${relative_path}"
+    "${PYTHON_BIN}" "${SCRIPT_DIR}/${relative_path}"
+}
+
+# Core one-dimensional simulations and their polarization comparisons.
+run_example "single_simulation/single_simulation.py"
+run_example "single_simulation/polarization_comparison.py"
+run_example "fixed_angle_sweep/fixed_angle_sweep.py"
+run_example "fixed_angle_sweep/polarization_comparison.py"
+run_example "monochromator_sweep/monochromator_sweep.py"
+run_example "monochromator_sweep/polarization_comparison.py"
+run_example "energy_angle_sweep/energy_angle_sweep.py"
+run_example "energy_angle_sweep/polarization_comparison.py"
+run_example "batch_user_cases/batch_user_cases.py"
+run_example "batch_user_cases/polarization_comparison.py"
+
+# Multilayer, convergence, and solver-comparison studies.
+run_example "blazed_multilayer_sweep/blazed_multilayer_sweep.py"
+run_example "blazed_multilayer_sweep/polarization_comparison.py"
+run_example "blazed_multilayer_memory_comparison/blazed_multilayer_memory_comparison.py"
+run_example "multilayer_theta_search/multilayer_theta_search.py"
+run_example "parameter_study/parameter_study.py"
+run_example "neviere_solver/neviere_solver.py"
+run_example "deep_grating_limits/deep_grating_limits.py"
+run_example "continuous_vs_staircase/continuous_vs_staircase.py"
+run_example "solver_runtime/solver_runtime.py"
+
+# This wrapper runs both roughness studies and re-generates their comparison
+# figures after their simulation outputs are available.
+echo "==> Running fixed_angle_roughness/run_roughness_examples.sh"
+PYTHON_BIN="${PYTHON_BIN}" bash "${SCRIPT_DIR}/fixed_angle_roughness/run_roughness_examples.sh"
+
+echo "==> All simulation examples completed"
diff --git a/examples/simulation/single_simulation/polarization_comparison.py b/examples/simulation/single_simulation/polarization_comparison.py
index 77a4de7..89aed83 100644
--- a/examples/simulation/single_simulation/polarization_comparison.py
+++ b/examples/simulation/single_simulation/polarization_comparison.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import argparse
 from pathlib import Path
 
 import matplotlib.pyplot as plt
@@ -18,7 +19,7 @@
     layer_material="Pt",
     layer_thickness_nm=28.77,
     x_resolution_nm=1.0,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
 )
 
 output_dir = Path(__file__).resolve().parent / "results"
@@ -29,7 +30,18 @@
 diffraction_order = 1
 fourier_orders = 5
 
+parser = argparse.ArgumentParser(description="Polarization comparison (s vs p)")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
+)
+args = parser.parse_args()
+
 result_s = grax.run_simulation(
+    solver=args.solver,
     grating=grating,
     energy_ev=energy_ev,
     grazing_angle_deg=grazing_angle_deg,
@@ -40,6 +52,7 @@
 )
 
 result_p = grax.run_simulation(
+    solver=args.solver,
     grating=grating,
     energy_ev=energy_ev,
     grazing_angle_deg=grazing_angle_deg,
@@ -49,7 +62,7 @@
     backend="numba",
 )
 
-comparison_plot_path = output_dir / "single_simulation_pol_comparison.png"
+comparison_plot_path = output_dir / f"single_simulation_pol_comparison_{args.solver}.png"
 
 orders = result_s.orders
 efficiency_s = np.asarray(result_s.efficiency_all, dtype=float)
diff --git a/examples/simulation/single_simulation/results/single_simulation.csv b/examples/simulation/single_simulation/results/single_simulation.csv
deleted file mode 100644
index 91bc1a3..0000000
--- a/examples/simulation/single_simulation/results/single_simulation.csv
+++ /dev/null
@@ -1,12 +0,0 @@
-case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
-single,200.0,4.0,-5,0.008190566573616083,9.88107865604465
-single,200.0,4.0,-4,0.0084915730314501,9.015622340555609
-single,200.0,4.0,-3,0.007761775618329491,8.058583440755712
-single,200.0,4.0,-2,0.02090601641551382,6.972349028947534
-single,200.0,4.0,-1,0.14872178397238886,5.683315135192018
-single,200.0,4.0,0,0.23513105391048855,4.000000000000043
-single,200.0,4.0,1,0.0,0.0
-single,200.0,4.0,2,0.0,0.0
-single,200.0,4.0,3,0.0,0.0
-single,200.0,4.0,4,0.0,0.0
-single,200.0,4.0,5,0.0,0.0
diff --git a/examples/simulation/single_simulation/results/single_simulation_neviere.csv b/examples/simulation/single_simulation/results/single_simulation_neviere.csv
new file mode 100644
index 0000000..a74652f
--- /dev/null
+++ b/examples/simulation/single_simulation/results/single_simulation_neviere.csv
@@ -0,0 +1,12 @@
+case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
+single,200.0,4.0,-5,0.0076665202874614535,9.88107865604465
+single,200.0,4.0,-4,0.00818714614951143,9.015622340555609
+single,200.0,4.0,-3,0.0073407172369143354,8.058583440755712
+single,200.0,4.0,-2,0.02042349795001465,6.972349028947534
+single,200.0,4.0,-1,0.1433640501654391,5.683315135192018
+single,200.0,4.0,0,0.22932799290493322,4.000000000000043
+single,200.0,4.0,1,0.0,0.0
+single,200.0,4.0,2,0.0,0.0
+single,200.0,4.0,3,0.0,0.0
+single,200.0,4.0,4,0.0,0.0
+single,200.0,4.0,5,0.0,0.0
diff --git a/examples/simulation/single_simulation/results/single_simulation_pol_comparison_rcwa.png b/examples/simulation/single_simulation/results/single_simulation_pol_comparison_rcwa.png
new file mode 100644
index 0000000..bc85d04
Binary files /dev/null and b/examples/simulation/single_simulation/results/single_simulation_pol_comparison_rcwa.png differ
diff --git a/examples/simulation/single_simulation/results/single_simulation_profile.png b/examples/simulation/single_simulation/results/single_simulation_profile.png
index 9cb0929..9cbb4db 100644
Binary files a/examples/simulation/single_simulation/results/single_simulation_profile.png and b/examples/simulation/single_simulation/results/single_simulation_profile.png differ
diff --git a/examples/simulation/single_simulation/results/single_simulation_rcwa.csv b/examples/simulation/single_simulation/results/single_simulation_rcwa.csv
new file mode 100644
index 0000000..6d82bbf
--- /dev/null
+++ b/examples/simulation/single_simulation/results/single_simulation_rcwa.csv
@@ -0,0 +1,12 @@
+case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
+single,200.0,4.0,-5,0.0078091132237791475,9.88107865604465
+single,200.0,4.0,-4,0.008237466727333023,9.015622340555609
+single,200.0,4.0,-3,0.0073968819786985746,8.058583440755712
+single,200.0,4.0,-2,0.02072069230373551,6.972349028947534
+single,200.0,4.0,-1,0.1441017563221078,5.683315135192018
+single,200.0,4.0,0,0.22667838562748438,4.000000000000043
+single,200.0,4.0,1,0.0,0.0
+single,200.0,4.0,2,0.0,0.0
+single,200.0,4.0,3,0.0,0.0
+single,200.0,4.0,4,0.0,0.0
+single,200.0,4.0,5,0.0,0.0
diff --git a/examples/simulation/single_simulation/single_simulation.py b/examples/simulation/single_simulation/single_simulation.py
index f026d6e..bb07e74 100644
--- a/examples/simulation/single_simulation/single_simulation.py
+++ b/examples/simulation/single_simulation/single_simulation.py
@@ -4,7 +4,6 @@
 
 from pathlib import Path
 import argparse
-
 import numpy as np
 import grax
 
@@ -18,13 +17,10 @@
     layer_material="Pt",
     layer_thickness_nm=28.77,
     x_resolution_nm=1.0,
-    z_resolution_nm=0.1,
+    z_resolution_nm=0.5,
 )
 
-parser = argparse.ArgumentParser(description="Run single RCWA simulation")
 output_dir = Path(__file__).resolve().parent / "results"
-
-args = parser.parse_args()
 output_dir.mkdir(parents=True, exist_ok=True)
 
 energy_ev = 200.0
@@ -32,7 +28,18 @@
 diffraction_order = 1
 fourier_orders = 5
 
+parser = argparse.ArgumentParser(description="Run a single grating simulation")
+parser.add_argument(
+    "--solver",
+    choices=("rcwa", "neviere"),
+    default="rcwa",
+    help="Electromagnetic solver to run. Both compute every diffraction order; "
+    "they differ only in how each layer is crossed in z.",
+)
+args = parser.parse_args()
+
 result = grax.run_simulation(
+    solver=args.solver,
     grating=grating,
     energy_ev=energy_ev,
     grazing_angle_deg=grazing_angle_deg,
@@ -42,7 +49,7 @@
     backend="numba",
 )
 
-csv_path = output_dir / "single_simulation.csv"
+csv_path = output_dir / f"single_simulation_{args.solver}.csv"
 grax.write_all_orders_csv(result, csv_path)
 
 profile_path = output_dir / "single_simulation_profile.png"
diff --git a/examples/simulation/solver_runtime/results/solver_runtime_full.csv b/examples/simulation/solver_runtime/results/solver_runtime_full.csv
new file mode 100644
index 0000000..8ac63c3
--- /dev/null
+++ b/examples/simulation/solver_runtime/results/solver_runtime_full.csv
@@ -0,0 +1,4 @@
+case,rcwa_seconds_per_point,neviere_seconds_per_point,speedup,max_abs_deviation
+laminar 400 l/mm,1.278882,0.427940,2.9885,1.348083e-11
+blazed 600 l/mm,0.887363,0.363466,2.4414,5.589584e-12
+blazed 2400 l/mm multilayer,5.598349,2.182976,2.5645,6.027401e-13
diff --git a/examples/simulation/solver_runtime/results/solver_runtime_full.png b/examples/simulation/solver_runtime/results/solver_runtime_full.png
new file mode 100644
index 0000000..4a34a2a
Binary files /dev/null and b/examples/simulation/solver_runtime/results/solver_runtime_full.png differ
diff --git a/examples/simulation/solver_runtime/results/solver_runtime_reduced.csv b/examples/simulation/solver_runtime/results/solver_runtime_reduced.csv
new file mode 100644
index 0000000..1c8cb4a
--- /dev/null
+++ b/examples/simulation/solver_runtime/results/solver_runtime_reduced.csv
@@ -0,0 +1,4 @@
+case,rcwa_seconds_per_point,neviere_seconds_per_point,speedup,max_abs_deviation
+laminar 400 l/mm,0.036166,0.024659,1.4667,5.182639e-11
+blazed 600 l/mm,0.043208,0.029887,1.4457,2.685445e-11
+blazed 2400 l/mm multilayer,0.049152,0.041899,1.1731,1.364908e-12
diff --git a/examples/simulation/solver_runtime/results/solver_runtime_reduced.png b/examples/simulation/solver_runtime/results/solver_runtime_reduced.png
new file mode 100644
index 0000000..1c5f519
Binary files /dev/null and b/examples/simulation/solver_runtime/results/solver_runtime_reduced.png differ
diff --git a/examples/simulation/solver_runtime/solver_runtime.py b/examples/simulation/solver_runtime/solver_runtime.py
new file mode 100644
index 0000000..eb3c4f2
--- /dev/null
+++ b/examples/simulation/solver_runtime/solver_runtime.py
@@ -0,0 +1,206 @@
+"""What the differential method costs compared with the modal solver.
+
+The differential method is usually the faster of the two, which is the opposite
+of what "integrate an ODE through every layer" suggests. The reason is that the
+modal solver eigen-decomposes each distinct layer operator, and a dense
+eigensolve on a 2N+1 basis is expensive. The differential method never does one:
+it advances a Runge-Kutta step and converts the result to an interface-response
+block, both of which are matrix products.
+
+The size of the gap depends on resolution, not on the grating. Measured here:
+
+    reduced resolution     1.2x to 1.4x
+    production resolution  2.4x to 3.0x
+
+Coarse runs have few distinct layers, so the eigensolve is not yet the dominant
+cost and the two solvers are close. Refine the grid and the modal solver pays for
+an eigensolve per distinct layer while the differential method does not, so the
+gap opens up. It is worth knowing that the advantage appears exactly in the
+regime where a sweep is expensive, and that a quick coarse benchmark understates
+it.
+
+A speed number means nothing on its own, so this example reports the maximum
+efficiency difference between the two solvers alongside each timing. If that
+number were large the comparison would be meaningless; it is around 1e-11.
+
+Run with --full for the production-resolution numbers above; the default is
+reduced so the example finishes quickly.
+"""
+
+from __future__ import annotations
+
+import argparse
+import time
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+import grax
+
+parser = argparse.ArgumentParser(description="Time the two solvers on several gratings")
+parser.add_argument(
+    "--full",
+    action="store_true",
+    help="Use production resolutions. Slower, and closer to what a real sweep costs.",
+)
+args = parser.parse_args()
+
+output_dir = Path(__file__).resolve().parent / "results"
+output_dir.mkdir(parents=True, exist_ok=True)
+
+ENERGIES_EV = [200.0, 400.0, 800.0]
+GRAZING_ANGLE_DEG = 4.0
+POLARIZATION = "p"
+
+
+def laminar_grating() -> grax.LaminarGrating:
+    """Return the 400 l/mm coated laminar grating."""
+
+    return grax.LaminarGrating(
+        period_lpermm=400,
+        width_to_period_ratio=0.67,
+        depth_nm=14.9,
+        left_wall_angle_deg=15.0,
+        right_wall_angle_deg=15.0,
+        substrate_material="Si",
+        layer_material="Pt",
+        layer_thickness_nm=28.77,
+        x_resolution_nm=0.1 if args.full else 1.0,
+        z_resolution_nm=0.1 if args.full else 0.5,
+    )
+
+
+def blazed_grating() -> grax.BlazedGrating:
+    """Return the 600 l/mm coated blazed grating."""
+
+    return grax.BlazedGrating(
+        period_lpermm=600,
+        blaze_angle_deg=0.729,
+        anti_blaze_angle_deg=5.597,
+        substrate_material="Si",
+        layer_material="Au",
+        layer_thickness_nm=30.0,
+        x_resolution_nm=0.1 if args.full else 1.0,
+        z_resolution_nm=0.1 if args.full else 0.5,
+    )
+
+
+def multilayer_grating() -> grax.BlazedGrating:
+    """Return a blazed grating on a Cr/C multilayer stack."""
+
+    carbon = "C"
+    return grax.BlazedGrating(
+        period_lpermm=2400,
+        blaze_angle_deg=1.37,
+        anti_blaze_angle_deg=3.25,
+        coating_stack=grax.MultilayerStack(
+            substrate_material="Si",
+            material_a="Cr",
+            material_b=carbon,
+            d_period_nm=4.8,
+            gamma=0.4,
+            n_bilayers=20 if args.full else 8,
+            top_material=carbon,
+        ),
+        x_resolution_nm=0.1 if args.full else 1.0,
+        z_resolution_nm=0.05 if args.full else 0.5,
+    )
+
+
+CASES = [
+    ("laminar 400 l/mm", laminar_grating, 25 if args.full else 10, 1),
+    ("blazed 600 l/mm", blazed_grating, 20 if args.full else 10, 1),
+    ("blazed 2400 l/mm multilayer", multilayer_grating, 25 if args.full else 10, 2),
+]
+
+
+def time_solver(grating, fourier_orders: int, diffraction_order: int, solver: str):
+    """Return seconds per point and the all-order efficiencies for one solver.
+
+    Args:
+        grating: Grating to solve.
+        fourier_orders: Fourier truncation order.
+        diffraction_order: Order reported in the result.
+        solver: ``"rcwa"`` or ``"neviere"``.
+
+    Returns:
+        Mean seconds per energy point and the stacked all-order efficiencies.
+    """
+
+    efficiencies = []
+    started = time.perf_counter()
+    for energy_ev in ENERGIES_EV:
+        result = grax.run_simulation(
+            grating=grating,
+            energy_ev=energy_ev,
+            grazing_angle_deg=GRAZING_ANGLE_DEG,
+            diffraction_order=diffraction_order,
+            fourier_orders=fourier_orders,
+            polarization=POLARIZATION,
+            solver=solver,
+            validate_physical_results=False,
+        )
+        efficiencies.append(np.asarray(result.efficiency_all, dtype=float))
+    elapsed = time.perf_counter() - started
+    return elapsed / len(ENERGIES_EV), np.vstack(efficiencies)
+
+
+rows = []
+print(f"Timing {len(ENERGIES_EV)} energies per case "
+      f"({'production' if args.full else 'reduced'} resolution).\n")
+print(f"{'case':<30} {'rcwa s/pt':>10} {'neviere s/pt':>13} {'speedup':>9} {'max |dE|':>11}")
+for label, build, fourier_orders, diffraction_order in CASES:
+    grating = build()
+    # Warm the numba Fourier kernel so the first case is not charged for the JIT.
+    grax.run_simulation(
+        grating=grating, energy_ev=ENERGIES_EV[0], grazing_angle_deg=GRAZING_ANGLE_DEG,
+        fourier_orders=4, polarization=POLARIZATION, validate_physical_results=False,
+    )
+    rcwa_seconds, rcwa_efficiency = time_solver(grating, fourier_orders, diffraction_order, "rcwa")
+    dm_seconds, dm_efficiency = time_solver(grating, fourier_orders, diffraction_order, "neviere")
+    deviation = float(np.max(np.abs(rcwa_efficiency - dm_efficiency)))
+    speedup = rcwa_seconds / dm_seconds
+    rows.append((label, rcwa_seconds, dm_seconds, speedup, deviation))
+    print(f"{label:<30} {rcwa_seconds:>10.3f} {dm_seconds:>13.3f} "
+          f"{speedup:>8.2f}x {deviation:>11.2e}")
+
+labels = [row[0] for row in rows]
+positions = np.arange(len(rows))
+figure, axis = plt.subplots(figsize=(10, 6))
+axis.barh(positions - 0.2, [row[1] for row in rows], height=0.36, label="RCWA (modal)")
+axis.barh(positions + 0.2, [row[2] for row in rows], height=0.36, label="Nevière (differential)")
+for index, row in enumerate(rows):
+    axis.annotate(f"{row[3]:.2f}x faster", xy=(max(row[1], row[2]), index),
+                  xytext=(6, 0), textcoords="offset points", va="center", fontsize=9)
+axis.set_yticks(positions)
+axis.set_yticklabels(labels)
+axis.set_xlabel("Seconds per energy point")
+axis.set_title(
+    "Solver runtime "
+    f"({'production' if args.full else 'reduced'} resolution); "
+    f"max efficiency difference {max(row[4] for row in rows):.1e}"
+)
+axis.grid(True, alpha=0.3, axis="x")
+axis.legend(loc="lower right")
+figure.tight_layout()
+
+suffix = "full" if args.full else "reduced"
+plot_path = output_dir / f"solver_runtime_{suffix}.png"
+figure.savefig(plot_path, dpi=150, bbox_inches="tight")
+plt.close(figure)
+
+csv_path = output_dir / f"solver_runtime_{suffix}.csv"
+with csv_path.open("w", encoding="utf-8") as handle:
+    handle.write("case,rcwa_seconds_per_point,neviere_seconds_per_point,speedup,max_abs_deviation\n")
+    for label, rcwa_seconds, dm_seconds, speedup, deviation in rows:
+        handle.write(f"{label},{rcwa_seconds:.6f},{dm_seconds:.6f},{speedup:.4f},{deviation:.6e}\n")
+
+print(f"\nSpeedup range: {min(row[3] for row in rows):.2f}x to {max(row[3] for row in rows):.2f}x")
+if not args.full:
+    print("Reduced resolution understates the gap; run with --full for production numbers.")
+print(f"Largest efficiency difference across all cases: {max(row[4] for row in rows):.2e}")
+print("The speedup is not bought with accuracy: the two solvers still agree to")
+print("roughly the level they agree to everywhere else.")
+print(f"Plot saved to: {plot_path}")
+print(f"CSV saved to: {csv_path}")
diff --git a/pyproject.toml b/pyproject.toml
index 2cf0270..5472ef8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -14,7 +14,7 @@ classifiers = [
   "Programming Language :: Python :: 3.13",
   "Programming Language :: Python :: 3 :: Only",
 ]
-license = { text = "MIT" }
+license = { text = "EUPL-1.2" }
 authors = [
   { name = "Simone Vadilonga", email = "simone.vadilonga@helmholtz-berlin.de" }
 ]
diff --git a/src/grax/__init__.py b/src/grax/__init__.py
index 7d0de73..6102036 100644
--- a/src/grax/__init__.py
+++ b/src/grax/__init__.py
@@ -13,6 +13,7 @@
     material_density_g_cm3,
 )
 from .gratings import BaseGrating, BlazedGrating, LaminarGrating, ProfileGrating
+from .simulation.core import normalize_polarization
 from .parameter_sweep import (
     ParameterStudyEnergyResult,
     ParameterStudyResult,
@@ -21,7 +22,7 @@
     plot_parameter_study,
     run_parameter_study,
 )
-from .rcwa_1d import res0, res1, res2
+from .solvers import NeviereOptions, res0, res1, res2, res2_dm
 from .roughness import RoughnessSpec
 from .stacks import (
     BaseStack,
@@ -69,6 +70,7 @@
     "LaminarGrating",
     "MultilayerThetaSearchSweepResult",
     "MultilayerStack",
+    "NeviereOptions",
     "ParameterStudyEnergyResult",
     "ParameterStudyResult",
     "ParameterSweepSeries",
@@ -93,12 +95,14 @@
     "material_density_g_cm3",
     "multilayer_theta_search_cases",
     "monochromator_cases",
+    "normalize_polarization",
     "monochromator_grazing_angles_deg",
     "plot_parameter_study",
     "plot_order_subset",
     "res0",
     "res1",
     "res2",
+    "res2_dm",
     "run_example_slag",
     "run_parameter_study",
     "run_multilayer_theta_search",
diff --git a/src/grax/gratings.py b/src/grax/gratings.py
index 0a354b8..47dd2a0 100644
--- a/src/grax/gratings.py
+++ b/src/grax/gratings.py
@@ -1,4 +1,4 @@
-"""Grating profile objects used by RCWA simulations."""
+"""Grating profile objects shared by both electromagnetic solvers."""
 
 from __future__ import annotations
 
@@ -429,7 +429,7 @@ def _texture_descriptor_for_row(
         n_inc: complex,
         n_sub: complex,
     ) -> object:
-        """Return one RCWA texture descriptor for a single solver row."""
+        """Return one texture descriptor for a single solver row."""
 
         row_values = self._refractive_index_row(
             z_value=z_value,
diff --git a/src/grax/parameter_sweep.py b/src/grax/parameter_sweep.py
index 2c1c7db..70d4cbb 100644
--- a/src/grax/parameter_sweep.py
+++ b/src/grax/parameter_sweep.py
@@ -14,7 +14,8 @@
 from tqdm import tqdm
 
 from .gratings import BaseGrating
-from .simulation import RCWASimulation
+from .simulation import GratingSimulation
+from .simulation.core import normalize_polarization
 
 __all__ = [
     "ParameterStudyEnergyResult",
@@ -127,6 +128,9 @@ def run_parameter_study(
     output_dir: str | Path | None = None,
     save_csv: bool = True,
     show_progress: bool = True,
+    solver: str = "rcwa",
+    solver_options: object | None = None,
+    backend: str = "numba",
 ) -> ParameterStudyResult:
     """Run a convergence study across Fourier orders and x/z discretization.
 
@@ -156,6 +160,14 @@ def run_parameter_study(
         output_dir: Optional directory for CSV exports. Creates subdirectory if needed.
         save_csv: Whether to export per-energy sweep CSV files to output_dir.
         show_progress: Whether to display progress bars during execution.
+        solver: Electromagnetic solver used for every point of the study.
+            ``"rcwa"`` (default) or ``"neviere"``.
+        solver_options: Integration settings for ``solver="neviere"``, as a
+            :class:`grax.NeviereOptions` or an equivalent mapping. Ignored by the
+            selected solver.
+        backend: Fourier coefficient backend selector. ``"numba"`` is the
+            default. Previously fixed internally; exposing it here makes a
+            convergence study reproducible against the backend it ran on.
 
     Returns:
         Structured parameter-study result containing all sweep data and metadata.
@@ -172,6 +184,7 @@ def run_parameter_study(
         >>> plot_parameter_study(result)
     """
 
+    polarization = normalize_polarization(polarization)
     default_fourier, default_x, default_z = get_default_parameter_study_ranges()
     fourier_values = np.asarray(
         default_fourier if fourier_orders_values is None else fourier_orders_values,
@@ -212,6 +225,9 @@ def run_parameter_study(
                 polarization=polarization,
                 max_retries=max_retries,
                 fixed_fourier_orders=fixed_fourier_orders,
+                solver=solver,
+                solver_options=solver_options,
+                backend=backend,
             ),
             "x_resolution_nm": _run_single_parameter_sweep(
                 grating=grating,
@@ -223,6 +239,9 @@ def run_parameter_study(
                 polarization=polarization,
                 max_retries=max_retries,
                 fixed_fourier_orders=fixed_fourier_orders,
+                solver=solver,
+                solver_options=solver_options,
+                backend=backend,
             ),
             "z_resolution_nm": _run_single_parameter_sweep(
                 grating=grating,
@@ -234,6 +253,9 @@ def run_parameter_study(
                 polarization=polarization,
                 max_retries=max_retries,
                 fixed_fourier_orders=fixed_fourier_orders,
+                solver=solver,
+                solver_options=solver_options,
+                backend=backend,
             ),
         }
         results.append(
@@ -394,10 +416,13 @@ def _run_single_parameter_sweep(
     polarization: str,
     max_retries: int,
     fixed_fourier_orders: int,
+    solver: str,
+    solver_options: object | None,
+    backend: str,
 ) -> ParameterSweepSeries:
     """Run one parameter sweep for one energy.
 
-    Executes a sequence of RCWA simulations varying one discretization parameter
+    Executes a sequence of simulations varying one discretization parameter
     while holding all others fixed. Implements retry logic for failed points with
     exponential backoff behavior (same parameters retried up to max_retries).
 
@@ -439,13 +464,15 @@ def _run_single_parameter_sweep(
                     case_grating = _clone_grating_with_override(grating, parameter, float(value))
                     fourier_orders = fixed_fourier_orders
 
-                result = RCWASimulation(
+                result = GratingSimulation(
                     grating=case_grating,
                     diffraction_order=diffraction_order,
                     fourier_orders=fourier_orders,
                     grazing_angle_deg=grazing_angle_deg,
                     polarization=polarization,
-                    backend="numba",
+                    backend=backend,
+                    solver=solver,
+                    solver_options=solver_options,
                 ).run_single(energy_ev)
                 efficiencies[index] = float(result["efficiency"])
                 success = True
diff --git a/src/grax/rcwa_1d.py b/src/grax/rcwa_1d.py
index 0b52d08..c31e252 100644
--- a/src/grax/rcwa_1d.py
+++ b/src/grax/rcwa_1d.py
@@ -1,1220 +1,99 @@
-from __future__ import annotations
+"""Backward-compatible aliases for the 1D solver internals.
+
+The solver implementation moved to the :mod:`grax.solvers` package when a second
+solver (the Nevière differential method) was added:
+
+- shared types, ``res0``/``res1``, the Fourier machinery, the layer field
+  operators, the interface cascade and the efficiency extraction now live in
+  :mod:`grax.solvers.common`
+- the modal RCWA layer solve and ``res2`` live in :mod:`grax.solvers.rcwa`
 
-import logging
-import hashlib
-from enum import Enum
-from dataclasses import dataclass, field
-from time import perf_counter
-from typing import Any, Dict, Literal, Tuple
+This module re-exports the historical names so existing imports of
+``grax.rcwa_1d`` keep working. New code should import from :mod:`grax.solvers`.
 
-from .simulation._profiling import SolverProfiler
+Note for tests and tooling: patching a name here rebinds only this alias module.
+To intercept a function the solvers actually call, patch it on the module that
+defines it (:mod:`grax.solvers.common` or :mod:`grax.solvers.rcwa`).
+"""
 
-import numpy as np
-from contextlib import nullcontext as _nullcontext
+from __future__ import annotations
 
-from .roughness import (
-    _apply_debye_waller_roughness as _apply_debye_waller_roughness_impl,
-    _debye_waller_roughness_factor as _debye_waller_roughness_factor_impl,
+from .roughness import (  # noqa: F401
     apply_debye_waller_roughness,
     debye_waller_roughness_diagnostics,
     incidence_sine_from_beta0,
 )
+from .solvers.common import (  # noqa: F401
+    ArrayLike,
+    BoundaryBlockCache,
+    DiffractionResult,
+    EigenCache,
+    FourierBackend,
+    FourierBackendName,
+    LayerFieldOperators,
+    Parameters,
+    Res1Parameters,
+    Res1Result,
+    Res2Parameters,
+    Res2Result,
+    Texture1D,
+    _angles_from_kx,
+    _apply_debye_waller_roughness,
+    _bottom_field_from_boundary_block,
+    _cascade_boundary_pair,
+    _cascade_layer_boundary_blocks,
+    _convert_texture,
+    _convolution_matrix,
+    _debye_waller_roughness_factor,
+    _incidence_sine_from_beta0,
+    _kz_branch,
+    _kz_branch_array,
+    _normalize_orders,
+    _piecewise_fourier_coefficients,
+    _piecewise_fourier_coefficients_baseline,
+    _piecewise_fourier_coefficients_numba,
+    _resolve_fourier_backend,
+    _texture_signature_for_metadata,
+    _top_admittance_from_boundary_block,
+    layer_field_operators,
+    res0,
+    res1,
+    safe_linalg_solve,
+)
+from .solvers.neviere import NeviereOptions, res2_dm  # noqa: F401
+from .solvers.rcwa import (  # noqa: F401
+    _layer_boundary_block,
+    _modal_function_matrices,
+    _modal_function_matrix,
+    _modal_q_coth,
+    _modal_q_csch,
+    _solve_te_stack,
+    _solve_tm_stack,
+    res2,
+)
 
-logger = logging.getLogger(__name__)
-
-
-ArrayLike = Any
-EigenCache = Dict[Tuple[Any, ...], Tuple[np.ndarray, np.ndarray]]
-BoundaryBlockCache = Dict[Tuple[Any, ...], np.ndarray]
-
-
-class FourierBackend(str, Enum):
-    """Internal Fourier coefficient implementations.
-
-    Two backends are available:
-    - NUMPY: Reference implementation kept for transition-time compatibility
-    - NUMBA: JIT-compiled kernel and the default production path
-    """
-
-    NUMPY = "numpy"
-    NUMBA = "numba"
-
-
-FourierBackendName = Literal["numpy", "numba"]
-
-try:
-    from numba import njit
-
-    _NUMBA_AVAILABLE = True
-except ImportError:  # pragma: no cover - optional dependency
-    njit = None
-    _NUMBA_AVAILABLE = False
-
-
-@dataclass
-class Res1Parameters:
-    trace: int = 0
-
-
-@dataclass
-class Res2Parameters:
-    result: int = 1
-
-
-@dataclass
-class Parameters:
-    dim: int = 1
-    polarization: int = 1
-    not_io: int = 0
-    res1: Res1Parameters = field(default_factory=Res1Parameters)
-    res2: Res2Parameters = field(default_factory=Res2Parameters)
-
-
-@dataclass
-class Texture1D:
-    period: float
-    breaks: np.ndarray
-    refractive_index: np.ndarray
-    epsilon_fourier: np.ndarray
-    homogeneous_index: complex | None = None
-    inv_epsilon_fourier: np.ndarray | None = None
-
-    @property
-    def signature(self) -> tuple[Any, ...]:
-        if self.homogeneous_index is not None:
-            n = self.homogeneous_index
-            return ("homogeneous", round(float(np.real(n)), 12), round(float(np.imag(n)), 12))
-        return (
-            "patterned",
-            tuple(np.round(self.breaks, 12)),
-            tuple((round(float(np.real(v)), 12), round(float(np.imag(v)), 12)) for v in self.refractive_index),
-        )
-
-
-@dataclass
-class Res1Result:
-    wavelength: float
-    period: float
-    orders: np.ndarray
-    beta0: float
-    polarization: int
-    textures: list[Texture1D]
-
-
-@dataclass
-class DiffractionResult:
-    order: np.ndarray
-    theta: np.ndarray
-    efficiency: np.ndarray
-    amplitude: np.ndarray
-
-
-@dataclass
-class Res2Result:
-    inc_top_reflected: DiffractionResult
-    inc_top_transmitted: DiffractionResult
-
-
-if _NUMBA_AVAILABLE:  # pragma: no branch
-    @njit(cache=True)
-    def _piecewise_fourier_coefficients_numba_kernel(
-        breaks: np.ndarray,
-        refractive_index: np.ndarray,
-        period: float,
-        max_order: int,
-    ) -> np.ndarray:
-        """Return Fourier coefficients using a Numba-compiled harmonic loop."""
-
-        harmonic_count = (2 * max_order) + 1
-        coeffs = np.zeros(harmonic_count, dtype=np.complex128)
-        epsilon = refractive_index**2
-        for harmonic_index in range(harmonic_count):
-            order = harmonic_index - max_order
-            if order == 0:
-                total = 0.0 + 0.0j
-                for segment_index in range(epsilon.size):
-                    total += epsilon[segment_index] * (breaks[segment_index + 1] - breaks[segment_index])
-                coeffs[harmonic_index] = total / period
-                continue
-
-            total = 0.0 + 0.0j
-            denominator = -1j * 2.0 * np.pi * order
-            for segment_index in range(epsilon.size):
-                phase_right = np.exp(-1j * 2.0 * np.pi * order * breaks[segment_index + 1] / period)
-                phase_left = np.exp(-1j * 2.0 * np.pi * order * breaks[segment_index] / period)
-                total += epsilon[segment_index] * (phase_right - phase_left) / denominator
-            coeffs[harmonic_index] = total
-        return coeffs
-
-
-def _resolve_fourier_backend(
-    backend: FourierBackendName | str,
-    profiler: SolverProfiler | None = None,
-) -> FourierBackend:
-    """Return the effective Fourier backend after validation."""
-
-    if backend == "numba" and not _NUMBA_AVAILABLE:
-        raise RuntimeError(
-            "numba backend requested but numba is not installed. "
-            "Reinstall the standard graxpy package so the required numba dependency is available."
-        )
-    try:
-        return FourierBackend(backend)
-    except ValueError as error:
-        raise ValueError(f"Unsupported Fourier backend: {backend}") from error
-
-
-def res0(dim: int) -> Parameters:
-    if dim == 0 or abs(dim) != 1:
-        raise NotImplementedError("The Python port currently supports 1D TE/TM-style entry only.")
-    return Parameters(dim=1, polarization=1 if dim > 0 else -1)
-
-
-def res1(
-    wavelength: float,
-    period: float,
-    textures: list[ArrayLike],
-    nn: int | tuple[int, int] | list[int],
-    beta0: float,
-    parm: Parameters | None = None,
-    *,
-    _profiler: SolverProfiler | None = None,
-    _fourier_backend: FourierBackendName | str = "numpy",
-) -> Res1Result:
-    parm = parm or res0(1)
-
-    with _profiler.record("res1_total") if _profiler is not None else _nullcontext():
-        orders = _normalize_orders(nn)
-        harmonic_count = (2 * int(np.max(np.abs(orders)))) + 1
-        resolved_backend = _resolve_fourier_backend(_fourier_backend, _profiler)
-        if _profiler is not None:
-            _profiler.set_metadata("fourier_backend_requested", str(_fourier_backend))
-            _profiler.set_metadata("fourier_backend_actual", resolved_backend.value)
-            _profiler.set_metadata("numba_available", _NUMBA_AVAILABLE)
-            _profiler.set_metadata("texture_count", len(textures))
-            _profiler.set_metadata("input_texture_count", len(textures))
-            _profiler.set_metadata("harmonic_count", harmonic_count)
-        unique_signatures = {_texture_signature_for_metadata(texture, period) for texture in textures}
-        if _profiler is not None:
-            _profiler.set_metadata("unique_texture_signatures", len(unique_signatures))
-        texture_cache: dict[tuple[Any, ...], Texture1D] = {}
-        converted: list[Texture1D] = []
-        cache_hits = 0
-        cache_misses = 0
-        max_order = 2 * int(np.max(np.abs(orders)))
-        for texture in textures:
-            cache_key = (
-                _texture_signature_for_metadata(texture, period),
-                float(period),
-                int(max_order),
-                resolved_backend.value,
-            )
-            if cache_key in texture_cache:
-                converted.append(texture_cache[cache_key])
-                cache_hits += 1
-                if _profiler is not None:
-                    _profiler.add_detail_count("texture_conversion_cache_hits", 1)
-                continue
-            converted_texture = _convert_texture(
-                texture,
-                period,
-                orders,
-                _profiler=_profiler,
-                _fourier_backend=resolved_backend,
-            )
-            texture_cache[cache_key] = converted_texture
-            converted.append(converted_texture)
-            cache_misses += 1
-            if _profiler is not None:
-                _profiler.add_detail_count("texture_conversion_cache_misses", 1)
-        if _profiler is not None:
-            _profiler.set_metadata("texture_conversion_cache_hits", cache_hits)
-            _profiler.set_metadata("texture_conversion_cache_misses", cache_misses)
-    return Res1Result(
-        wavelength=float(wavelength),
-        period=float(period),
-        orders=orders,
-        beta0=float(beta0),
-        polarization=parm.polarization,
-        textures=converted,
-    )
-
-
-def res2(
-    aa: Res1Result,
-    profile: tuple[ArrayLike, ArrayLike],
-    parm: Parameters | None = None,
-    *,
-    roughness_sigma_nm: float | None = None,
-    _profiler: SolverProfiler | None = None,
-) -> Res2Result:
-    """Solve the RCWA layer stack.
-
-    Args:
-        aa: Fourier-space texture data returned by :func:`res1`.
-        profile: Thickness and texture-index profile for one RCWA layer stack.
-        parm: Optional solver parameters.
-        roughness_sigma_nm: Optional rms interface roughness in nanometers. When
-            provided, reflected and transmitted diffraction efficiencies are
-            uniformly damped by a scalar Debye-Waller factor,
-            ``exp(-(4*pi*sigma*sin(theta)/wavelength)^2)``. Here ``theta`` is
-            the grazing incidence angle from the surface. This simple model
-            reduces total intensity to mimic scattering losses; it does not
-            alter geometry, RCWA matrices, diffraction amplitudes, or introduce
-            stochastic rough surfaces.
-
-    Returns:
-        Reflected and transmitted diffraction results for incidence from top.
-    """
-
-    if roughness_sigma_nm is not None and roughness_sigma_nm < 0.0:
-        raise ValueError("roughness_sigma_nm must be >= 0 when provided.")
-
-    # Polarization comes from aa (set by res1); parm is ignored for polarization selection.
-    polarization = aa.polarization
-
-    thicknesses = np.asarray(profile[0], dtype=float)
-    texture_indices = np.asarray(profile[1], dtype=int)
-    if thicknesses.shape != texture_indices.shape:
-        raise ValueError("Profile thicknesses and texture indices must have the same length.")
-    if len(texture_indices) < 2:
-        raise ValueError("The profile must contain at least superstrate and substrate textures.")
-
-    top_texture = aa.textures[int(texture_indices[0])]
-    bottom_texture = aa.textures[int(texture_indices[-1])]
-    if top_texture.homogeneous_index is None or bottom_texture.homogeneous_index is None:
-        raise ValueError("The Python port expects homogeneous superstrate and substrate textures.")
-
-    compressed: list[tuple[float, Texture1D]] = []
-    for thickness, texture_index in zip(thicknesses[1:-1], texture_indices[1:-1]):
-        if thickness <= 0:
-            continue
-        texture = aa.textures[int(texture_index)]
-        if compressed and compressed[-1][1].signature == texture.signature:
-            compressed[-1] = (compressed[-1][0] + float(thickness), texture)
-        else:
-            compressed.append((float(thickness), texture))
-
-    with _profiler.record("res2_total") if _profiler is not None else _nullcontext():
-        stack_solver = _solve_te_stack if polarization == 1 else _solve_tm_stack
-        reflected, transmitted = stack_solver(
-            wavelength=aa.wavelength,
-            period=aa.period,
-            orders=aa.orders,
-            beta0=aa.beta0,
-            n_top=top_texture.homogeneous_index,
-            n_bottom=bottom_texture.homogeneous_index,
-            layers=compressed,
-            _profiler=_profiler,
-        )
-    if roughness_sigma_nm is not None:
-        diagnostics = debye_waller_roughness_diagnostics(
-            sigma_nm=float(roughness_sigma_nm),
-            wavelength_nm=aa.wavelength,
-            beta0=float(aa.beta0),
-            theta_surface_rad=float(np.arccos(np.clip(float(aa.beta0), -1.0, 1.0))),
-        )
-        logger.debug(
-            "Debye-Waller roughness diagnostics: "
-            "sigma_nm=%(sigma_nm).6g, wavelength_nm=%(wavelength_nm).6g, "
-            "theta_surface_rad=%(theta_surface_rad).6g, "
-            "theta_normal_rad=%(theta_normal_rad).6g, "
-            "beta0=%(beta0).6g, sin_theta_used=%(sin_theta_used).6g, A=%(A).6g, "
-            "A_squared=%(A_squared).6g, damping_factor=%(damping_factor).6g",
-            diagnostics,
-        )
-        reflected, transmitted = apply_debye_waller_roughness(
-            reflected=reflected,
-            transmitted=transmitted,
-            wavelength_nm=aa.wavelength,
-            beta0=float(aa.beta0),
-            roughness_sigma_nm=float(roughness_sigma_nm),
-        )
-
-    return Res2Result(
-        inc_top_reflected=reflected,
-        inc_top_transmitted=transmitted,
-    )
-
-
-def _apply_debye_waller_roughness(
-    result: DiffractionResult,
-    *,
-    wavelength_nm: float,
-    incidence_sine: float,
-    roughness_sigma_nm: float,
-) -> DiffractionResult:
-    """Compatibility wrapper for the extracted roughness module."""
-
-    return _apply_debye_waller_roughness_impl(
-        result,
-        wavelength_nm=wavelength_nm,
-        incidence_sine=incidence_sine,
-        roughness_sigma_nm=roughness_sigma_nm,
-    )
-
-
-def _debye_waller_roughness_factor(
-    *,
-    wavelength_nm: float,
-    incidence_sine: float,
-    roughness_sigma_nm: float | None,
-) -> float:
-    """Compatibility wrapper for the extracted roughness module."""
-
-    return _debye_waller_roughness_factor_impl(
-        wavelength_nm=wavelength_nm,
-        incidence_sine=incidence_sine,
-        roughness_sigma_nm=roughness_sigma_nm,
-    )
-
-
-def _incidence_sine_from_beta0(beta0: float) -> float:
-    """Compatibility wrapper for the extracted roughness module."""
-
-    return incidence_sine_from_beta0(beta0)
-
-
-def _normalize_orders(nn: int | tuple[int, int] | list[int]) -> np.ndarray:
-    if np.isscalar(nn):
-        n = int(nn)
-        return np.arange(-n, n + 1, dtype=int)
-    values = np.asarray(nn, dtype=int).ravel()
-    if values.size != 2:
-        raise ValueError("Only scalar or two-value 1D order definitions are supported.")
-    return np.arange(values[0], values[1] + 1, dtype=int)
-
-
-def _convert_texture(
-    texture: ArrayLike,
-    period: float,
-    orders: np.ndarray,
-    *,
-    _profiler: SolverProfiler | None = None,
-    _fourier_backend: FourierBackend = FourierBackend.NUMPY,
-) -> Texture1D:
-    if not isinstance(texture, (list, tuple)):
-        refractive_index = complex(texture)
-        _breaks = np.array([0.0, period], dtype=float)
-        _n = np.array([refractive_index], dtype=complex)
-        _max_order = 2 * int(np.max(np.abs(orders)))
-        return Texture1D(
-            period=period,
-            breaks=_breaks,
-            refractive_index=_n,
-            epsilon_fourier=_piecewise_fourier_coefficients(
-                _breaks, _n, period=period, max_order=_max_order,
-                _profiler=_profiler, _fourier_backend=_fourier_backend,
-            ),
-            homogeneous_index=refractive_index,
-            inv_epsilon_fourier=_piecewise_fourier_coefficients(
-                _breaks, 1.0 / _n, period=period, max_order=_max_order,
-                _profiler=None, _fourier_backend=_fourier_backend,
-            ),
-        )
-
-    if len(texture) == 1:
-        refractive_index = complex(texture[0])
-        return _convert_texture(
-            refractive_index,
-            period,
-            orders,
-            _profiler=_profiler,
-            _fourier_backend=_fourier_backend,
-        )
-
-    if len(texture) != 2:
-        raise ValueError("1D Python textures must be homogeneous or [x_positions, n_left].")
-
-    x_positions = np.asarray(texture[0], dtype=float).ravel()
-    n_left = np.asarray(texture[1], dtype=complex).ravel()
-    if x_positions.size != n_left.size:
-        raise ValueError("Texture boundary and refractive-index vectors must have the same length.")
-    if x_positions.size == 0:
-        raise ValueError("Patterned textures require at least one discontinuity.")
-
-    breaks = np.concatenate(([0.0], x_positions, [period]))
-    refractive_index = np.concatenate((n_left, [n_left[0]]))
-    _max_order = 2 * int(np.max(np.abs(orders)))
-    return Texture1D(
-        period=period,
-        breaks=breaks,
-        refractive_index=refractive_index,
-        epsilon_fourier=_piecewise_fourier_coefficients(
-            breaks, refractive_index, period=period, max_order=_max_order,
-            _profiler=_profiler, _fourier_backend=_fourier_backend,
-        ),
-        inv_epsilon_fourier=_piecewise_fourier_coefficients(
-            breaks, 1.0 / refractive_index, period=period, max_order=_max_order,
-            _profiler=None, _fourier_backend=_fourier_backend,
-        ),
-    )
-
-
-def _texture_signature_for_metadata(texture: ArrayLike, period: float) -> tuple[Any, ...]:
-    """Return a hashable texture signature for one ``res1`` call."""
-
-    if not isinstance(texture, (list, tuple)):
-        value = complex(texture)
-        return ("homogeneous", round(float(np.real(value)), 12), round(float(np.imag(value)), 12))
-
-    if len(texture) == 1:
-        value = complex(texture[0])
-        return ("homogeneous", round(float(np.real(value)), 12), round(float(np.imag(value)), 12))
-
-    x_positions = np.asarray(texture[0], dtype=float).ravel()
-    n_left = np.asarray(texture[1], dtype=complex).ravel()
-    breaks = np.concatenate(([0.0], x_positions, [period]))
-    refractive_index = np.concatenate((n_left, [n_left[0]]))
-    return (
-        "patterned",
-        tuple(np.round(breaks, 12)),
-        tuple(
-            (round(float(np.real(value)), 12), round(float(np.imag(value)), 12))
-            for value in refractive_index
-        ),
-    )
-
-
-def _record_fourier_array_allocations(
-    profiler: SolverProfiler | None,
-    *arrays: np.ndarray,
-) -> None:
-    """Record temporary allocation estimates for Fourier helpers."""
-
-    if profiler is None:
-        return
-    bytes_total = sum(int(array.nbytes) for array in arrays)
-    profiler.add_detail_count("fourier_allocation_bytes", bytes_total)
-    profiler.update_detail_peak("fourier_temp_buffer_bytes_peak", float(bytes_total))
-
-
-
-
-
-def _record_fourier_common_stats(
-    profiler: SolverProfiler | None,
-    refractive_index: np.ndarray,
-    breaks: np.ndarray,
-    max_order: int,
-    backend: FourierBackend,
-) -> None:
-    """Record common Fourier call metadata and counters."""
-
-    if profiler is None:
-        return
-    profiler.add_detail_count("fourier_calls", 1)
-    profiler.add_detail_count("fourier_harmonics_total", (2 * max_order) + 1)
-    profiler.add_detail_count("fourier_segments_total", int(refractive_index.size))
-    profiler.add_detail_count("fourier_backend_calls", 1)
-    profiler.add_unique_value("fourier_backend_actual", backend.value)
-    profiler.update_detail_peak("fourier_segment_count_peak", float(refractive_index.size))
-    profiler.update_detail_peak("fourier_harmonic_count_peak", float((2 * max_order) + 1))
-    _record_fourier_array_allocations(profiler, refractive_index, breaks)
-
-
-def _record_fourier_call_totals(
-    profiler: SolverProfiler | None,
-    total_seconds: float,
-    exp_seconds: float,
-    sum_seconds: float,
-) -> None:
-    """Record comparable detailed Fourier timings across backends."""
-
-    if profiler is None:
-        return
-    overhead_seconds = max(0.0, total_seconds - exp_seconds - sum_seconds)
-    profiler.add_detail_timing("fourier_call_total", total_seconds)
-    profiler.add_detail_timing("fourier_exp", exp_seconds)
-    profiler.add_detail_timing("fourier_sum", sum_seconds)
-    profiler.add_detail_timing("fourier_loop_overhead", overhead_seconds)
-
-
-def _piecewise_fourier_coefficients_baseline(
-    breaks: np.ndarray,
-    refractive_index: np.ndarray,
-    period: float,
-    max_order: int,
-    *,
-    profiler: SolverProfiler | None,
-) -> np.ndarray:
-    """Return Fourier coefficients using the legacy harmonic loop."""
-
-    call_start = perf_counter() if profiler is not None else None
-    g = np.arange(-max_order, max_order + 1, dtype=int)
-    epsilon = refractive_index**2
-    coeffs = np.zeros_like(g, dtype=complex)
-    _record_fourier_array_allocations(profiler, g, epsilon, coeffs)
-
-    exp_seconds = 0.0
-    sum_seconds = 0.0
-    for idx, order in enumerate(g):
-        if profiler is not None:
-            profiler.add_detail_count("fourier_loop_iterations", 1)
-        if order == 0:
-            t0 = perf_counter() if profiler is not None else None
-            coeffs[idx] = np.sum(epsilon * (breaks[1:] - breaks[:-1])) / period
-            if profiler is not None and t0 is not None:
-                sum_seconds += perf_counter() - t0
-                profiler.add_detail_count("fourier_sum_calls", 1)
-            continue
-
-        t0 = perf_counter() if profiler is not None else None
-        phase_right = np.exp(-1j * 2.0 * np.pi * order * breaks[1:] / period)
-        phase_left = np.exp(-1j * 2.0 * np.pi * order * breaks[:-1] / period)
-        if profiler is not None and t0 is not None:
-            exp_seconds += perf_counter() - t0
-            profiler.add_detail_count("fourier_exp_calls", int(phase_right.size + phase_left.size))
-            _record_fourier_array_allocations(profiler, phase_right, phase_left)
-
-        t1 = perf_counter() if profiler is not None else None
-        coeffs[idx] = np.sum(
-            epsilon * (phase_right - phase_left) / (-1j * 2.0 * np.pi * order)
-        )
-        if profiler is not None and t1 is not None:
-            sum_seconds += perf_counter() - t1
-            profiler.add_detail_count("fourier_sum_calls", 1)
-
-    if profiler is not None and call_start is not None:
-        _record_fourier_call_totals(profiler, perf_counter() - call_start, exp_seconds, sum_seconds)
-    return coeffs
-
-
-
-
-
-
-
-
-def _piecewise_fourier_coefficients_numba(
-    breaks: np.ndarray,
-    refractive_index: np.ndarray,
-    period: float,
-    max_order: int,
-    *,
-    profiler: SolverProfiler | None,
-) -> np.ndarray:
-    """Return Fourier coefficients using the Numba kernel."""
-
-    call_start = perf_counter() if profiler is not None else None
-    coeffs = _piecewise_fourier_coefficients_numba_kernel(breaks, refractive_index, period, max_order)
-    if profiler is not None:
-        profiler.add_detail_count("fourier_loop_iterations", int((2 * max_order) + 1))
-        profiler.add_detail_count("fourier_numba_calls", 1)
-        profiler.add_detail_count("fourier_sum_calls", int((2 * max_order) + 1))
-        profiler.add_detail_count("fourier_exp_calls", int((2 * max_order) * 2 * refractive_index.size))
-        _record_fourier_array_allocations(profiler, coeffs)
-    if profiler is not None and call_start is not None:
-        total_seconds = perf_counter() - call_start
-        _record_fourier_call_totals(profiler, total_seconds, total_seconds, 0.0)
-    return coeffs
-
-
-def _piecewise_fourier_coefficients(
-    breaks: np.ndarray,
-    refractive_index: np.ndarray,
-    period: float,
-    max_order: int,
-    *,
-    _profiler: SolverProfiler | None = None,
-    _fourier_backend: FourierBackend = FourierBackend.NUMPY,
-) -> np.ndarray:
-    with _profiler.record("fourier_coefficients") if _profiler is not None else _nullcontext():
-        _record_fourier_common_stats(_profiler, refractive_index, breaks, max_order, _fourier_backend)
-        if _fourier_backend is FourierBackend.NUMPY:
-            return _piecewise_fourier_coefficients_baseline(
-                breaks,
-                refractive_index,
-                period,
-                max_order,
-                profiler=_profiler,
-            )
-        if _fourier_backend is FourierBackend.NUMBA:
-            return _piecewise_fourier_coefficients_numba(
-                breaks,
-                refractive_index,
-                period,
-                max_order,
-                profiler=_profiler,
-            )
-        raise ValueError(f"Unsupported Fourier backend: {_fourier_backend}")
-
-
-def _convolution_matrix(coefficients: np.ndarray, orders: np.ndarray) -> np.ndarray:
-    max_order = (len(coefficients) - 1) // 2
-    coefficient_indices = orders[:, np.newaxis] - orders[np.newaxis, :] + max_order
-    return coefficients[coefficient_indices]
-
-
-def _solve_te_stack(
-    wavelength: float,
-    period: float,
-    orders: np.ndarray,
-    beta0: float,
-    n_top: complex,
-    n_bottom: complex,
-    layers: list[tuple[float, Texture1D]],
-    *,
-    _profiler: SolverProfiler | None = None,
-) -> tuple[DiffractionResult, DiffractionResult]:
-    """Solve the 1D TE stack.
-
-    Each finite layer is represented by its Dirichlet-to-Neumann boundary block.
-    Blocks are cascaded by eliminating shared interface fields.
-    """
-
-    k0 = 2 * np.pi / wavelength
-    kx = k0 * beta0 + (2 * np.pi * orders / period)
-    kx_matrix_sq = np.diag(kx**2)
-    basis_size = len(orders)
-
-    kz_top = _kz_branch_array((k0 * n_top) ** 2 - kx**2)
-    kz_bottom = _kz_branch_array((k0 * n_bottom) ** 2 - kx**2)
-    derivative_top = 1j * np.diag(kz_top)
-    derivative_bottom = 1j * np.diag(kz_bottom)
-
-    eigen_cache: EigenCache = {}
-    boundary_block_cache: BoundaryBlockCache = {}
-    stack_boundary: np.ndarray | None = None
-    with _profiler.record("layer_propagation_cascade") if _profiler is not None else _nullcontext():
-        for thickness, texture in layers:
-            block = _layer_boundary_block(
-                thickness=thickness,
-                texture=texture,
-                orders=orders,
-                k0=k0,
-                kx=kx,
-                kx_matrix_sq=kx_matrix_sq,
-                polarization=1,
-                eigen_cache=eigen_cache,
-                boundary_block_cache=boundary_block_cache,
-                _profiler=_profiler,
-            )
-            if _profiler is not None:
-                _profiler.add_detail_count("layer_boundary_blocks_constructed", 1)
-                _profiler.update_detail_peak("layer_boundary_block_temp_peak", 1.0)
-                _profiler.update_detail_peak("layer_boundary_block_bytes_peak", float(block.nbytes))
-            if stack_boundary is None:
-                stack_boundary = block
-                continue
-            stack_boundary = _cascade_boundary_pair(
-                stack_boundary,
-                block,
-                basis_size,
-                _profiler=_profiler,
-            )
-    top_stack_admittance = _top_admittance_from_boundary_block(
-        stack_boundary=stack_boundary,
-        derivative_bottom=derivative_bottom,
-    )
-
-    incident = np.zeros(basis_size, dtype=complex)
-    incident[np.where(orders == 0)[0][0]] = 1.0
-
-    with _profiler.record("matrix_solves") if _profiler is not None else _nullcontext():
-        reflected_amplitude = np.linalg.solve(
-            derivative_top + top_stack_admittance,
-            (derivative_top - top_stack_admittance) @ incident,
-        )
-    top_field = incident + reflected_amplitude
-    transmitted_amplitude = _bottom_field_from_boundary_block(
-        top_field=top_field,
-        stack_boundary=stack_boundary,
-        derivative_bottom=derivative_bottom,
-        _profiler=_profiler,
-    )
-
-    incident_kz = kz_top[np.where(orders == 0)[0][0]]
-    reflected_efficiency = np.real(kz_top / incident_kz) * np.abs(reflected_amplitude) ** 2
-    transmitted_efficiency = np.real(kz_bottom / incident_kz) * np.abs(transmitted_amplitude) ** 2
-
-    reflected_theta = _angles_from_kx(kx, k0, n_top)
-    transmitted_theta = _angles_from_kx(kx, k0, n_bottom)
-
-    return (
-        DiffractionResult(
-            order=orders.copy(),
-            theta=reflected_theta,
-            efficiency=reflected_efficiency,
-            amplitude=reflected_amplitude,
-        ),
-        DiffractionResult(
-            order=orders.copy(),
-            theta=transmitted_theta,
-            efficiency=transmitted_efficiency,
-            amplitude=transmitted_amplitude,
-        ),
-    )
-
-
-def _solve_tm_stack(
-    wavelength: float,
-    period: float,
-    orders: np.ndarray,
-    beta0: float,
-    n_top: complex,
-    n_bottom: complex,
-    layers: list[tuple[float, Texture1D]],
-    *,
-    _profiler: SolverProfiler | None = None,
-) -> tuple[DiffractionResult, DiffractionResult]:
-    """Solve the 1D TM stack.
-
-    Uses the inverse-permittivity convolution operator and TM boundary admittances.
-    Structure mirrors _solve_te_stack; only the layer operator and semi-infinite
-    derivatives differ.
-    """
-
-    k0 = 2 * np.pi / wavelength
-    kx = k0 * beta0 + (2 * np.pi * orders / period)
-    kx_matrix_sq = np.diag(kx**2)
-    basis_size = len(orders)
-
-    kz_top = _kz_branch_array((k0 * n_top) ** 2 - kx**2)
-    kz_bottom = _kz_branch_array((k0 * n_bottom) ** 2 - kx**2)
-    derivative_top = 1j * np.diag(kz_top / n_top**2)
-    derivative_bottom = 1j * np.diag(kz_bottom / n_bottom**2)
-
-    eigen_cache: EigenCache = {}
-    boundary_block_cache: BoundaryBlockCache = {}
-    stack_boundary: np.ndarray | None = None
-    with _profiler.record("layer_propagation_cascade") if _profiler is not None else _nullcontext():
-        for thickness, texture in layers:
-            block = _layer_boundary_block(
-                thickness=thickness,
-                texture=texture,
-                orders=orders,
-                k0=k0,
-                kx=kx,
-                kx_matrix_sq=kx_matrix_sq,
-                polarization=-1,
-                eigen_cache=eigen_cache,
-                boundary_block_cache=boundary_block_cache,
-                _profiler=_profiler,
-            )
-            if _profiler is not None:
-                _profiler.add_detail_count("layer_boundary_blocks_constructed", 1)
-                _profiler.update_detail_peak("layer_boundary_block_temp_peak", 1.0)
-                _profiler.update_detail_peak("layer_boundary_block_bytes_peak", float(block.nbytes))
-            if stack_boundary is None:
-                stack_boundary = block
-                continue
-            stack_boundary = _cascade_boundary_pair(
-                stack_boundary,
-                block,
-                basis_size,
-                _profiler=_profiler,
-            )
-    top_stack_admittance = _top_admittance_from_boundary_block(
-        stack_boundary=stack_boundary,
-        derivative_bottom=derivative_bottom,
-    )
-
-    incident = np.zeros(basis_size, dtype=complex)
-    incident[np.where(orders == 0)[0][0]] = 1.0
-
-    with _profiler.record("matrix_solves") if _profiler is not None else _nullcontext():
-        reflected_amplitude = np.linalg.solve(
-            derivative_top + top_stack_admittance,
-            (derivative_top - top_stack_admittance) @ incident,
-        )
-    top_field = incident + reflected_amplitude
-    transmitted_amplitude = _bottom_field_from_boundary_block(
-        top_field=top_field,
-        stack_boundary=stack_boundary,
-        derivative_bottom=derivative_bottom,
-        _profiler=_profiler,
-    )
-
-    incident_idx = np.where(orders == 0)[0][0]
-    incident_kz = kz_top[incident_idx]
-    # TM Poynting flux ~ Re(kz/n²); normalise by incident admittance Re(kz_inc/n_top²)
-    incident_admittance = np.real(incident_kz / n_top**2)
-    reflected_efficiency = np.real(kz_top / n_top**2) / incident_admittance * np.abs(reflected_amplitude) ** 2
-    transmitted_efficiency = np.real(kz_bottom / n_bottom**2) / incident_admittance * np.abs(transmitted_amplitude) ** 2
-
-    reflected_theta = _angles_from_kx(kx, k0, n_top)
-    transmitted_theta = _angles_from_kx(kx, k0, n_bottom)
-
-    return (
-        DiffractionResult(
-            order=orders.copy(),
-            theta=reflected_theta,
-            efficiency=reflected_efficiency,
-            amplitude=reflected_amplitude,
-        ),
-        DiffractionResult(
-            order=orders.copy(),
-            theta=transmitted_theta,
-            efficiency=transmitted_efficiency,
-            amplitude=transmitted_amplitude,
-        ),
-    )
-
-
-def _layer_boundary_block(
-    *,
-    thickness: float,
-    texture: Texture1D,
-    orders: np.ndarray,
-    k0: float,
-    kx: np.ndarray,
-    kx_matrix_sq: np.ndarray,
-    polarization: int = 1,
-    eigen_cache: EigenCache,
-    boundary_block_cache: BoundaryBlockCache,
-    _profiler: SolverProfiler | None = None,
-) -> np.ndarray:
-    """Return the interface-response block for one finite RCWA layer."""
-
-    basis_size = len(orders)
-    logger.debug(f"  _layer_boundary_block: thickness={thickness:.4f} nm, basis_size={basis_size}")
-
-    if basis_size > 201:
-        raise ValueError(f"Fourier orders too large: {basis_size} modes. "
-                        "Try reducing fourier_orders to 50 or less.")
-
-    boundary_cache_key = (
-        texture.signature,
-        float(thickness),
-        tuple(int(order) for order in orders),
-        float(k0),
-        int(polarization),
-    )
-    cached_block = boundary_block_cache.get(boundary_cache_key)
-    if cached_block is not None:
-        if _profiler is not None:
-            _profiler.add_detail_count("layer_boundary_block_cache_hits", 1)
-        return cached_block
-    if _profiler is not None:
-        _profiler.add_detail_count("layer_boundary_block_cache_misses", 1)
-
-    inv_epsilon_conv_tm: np.ndarray | None = None
-    with _profiler.record("layer_operator_build") if _profiler is not None else _nullcontext():
-        epsilon_conv = _convolution_matrix(texture.epsilon_fourier, orders)
-        if polarization == 1:
-            operator = kx_matrix_sq - (k0**2) * epsilon_conv
-        else:
-            # TM: Li factorization — A = a1 @ a2
-            # a2 = kx @ inv([ε]) @ kx - k0² I
-            # a1 = inv([1/ε])
-            # The correct eigenproblem is a1*a2 (not a2*a1), consistent with
-            # dH/dz = ik0*a1*E_x and dE_x/dz = ik0*a2*H → d²H/dz² = -k0²*a1*a2*H.
-            kx_diag = np.diag(kx)
-            inv_epsilon_conv_tm = _convolution_matrix(texture.inv_epsilon_fourier, orders)
-            inv_eps_matrix = np.linalg.inv(epsilon_conv)
-            inv_inveps_matrix = np.linalg.inv(inv_epsilon_conv_tm)
-            a2 = kx_diag @ inv_eps_matrix @ kx_diag - (k0**2) * np.eye(basis_size)
-            operator = inv_inveps_matrix @ a2
-        if np.any(np.isnan(operator)) or np.any(np.isinf(operator)):
-            raise ValueError("Layer operator contains NaN/Inf values")
-
-    cache_key = (
-        texture.signature,
-        tuple(int(order) for order in orders),
-        float(k0),
-        int(polarization),
-    )
-    if _profiler is not None:
-        operator_key = hashlib.sha1(operator.tobytes()).hexdigest()
-        _profiler.add_unique_value("layer_operator_unique", operator_key)
-        _profiler.add_detail_count("layer_operator_rows_total", int(operator.shape[0]))
-        _profiler.add_detail_count("layer_operator_cols_total", int(operator.shape[1]))
-        _profiler.add_detail_count("layer_operator_calls", 1)
-        _profiler.update_detail_peak("layer_operator_rows_peak", float(operator.shape[0]))
-        _profiler.update_detail_peak("layer_operator_cols_peak", float(operator.shape[1]))
-    if cache_key in eigen_cache:
-        eigenvalues, eigenvectors = eigen_cache[cache_key]
-        if _profiler is not None:
-            _profiler.add_detail_count("layer_eigensolve_cache_hits", 1)
-    else:
-        if _profiler is not None:
-            _profiler.add_detail_count("layer_eigensolve_cache_misses", 1)
-        with _profiler.record("layer_eigensolve") if _profiler is not None else _nullcontext():
-            t0 = perf_counter() if _profiler is not None else None
-            eigenvalues, eigenvectors = np.linalg.eig(operator)
-            if _profiler is not None and t0 is not None:
-                _profiler.add_detail_timing("layer_eigensolve_call", perf_counter() - t0)
-        eigen_cache[cache_key] = (eigenvalues, eigenvectors)
-    if _profiler is not None:
-        _profiler.increment("layer_eigensolve_calls")
-
-    with _profiler.record("layer_modal_values") if _profiler is not None else _nullcontext():
-        q_values = np.sqrt(eigenvalues + 0j)
-        q_coth = _modal_q_coth(q_values, thickness)
-        q_csch = _modal_q_csch(q_values, thickness)
-    with _profiler.record("layer_modal_matrices") if _profiler is not None else _nullcontext():
-        t0 = perf_counter() if _profiler is not None else None
-        admittance, coupling = _modal_function_matrices(eigenvectors, q_coth, q_csch)
-        if _profiler is not None and t0 is not None:
-            _profiler.add_detail_timing("layer_modal_matrices_call", perf_counter() - t0)
-            _profiler.add_detail_count("layer_modal_matrices_calls", 1)
-    with _profiler.record("layer_block_assembly") if _profiler is not None else _nullcontext():
-        if polarization == -1 and inv_epsilon_conv_tm is not None:
-            # TM: block tracks [H; E_x] where E_x = [1/ε] @ ∂H/∂z
-            admittance = inv_epsilon_conv_tm @ admittance
-            coupling = inv_epsilon_conv_tm @ coupling
-        block = np.empty((2 * basis_size, 2 * basis_size), dtype=complex)
-        block[:basis_size, :basis_size] = -admittance
-        block[:basis_size, basis_size:] = coupling
-        block[basis_size:, :basis_size] = -coupling
-        block[basis_size:, basis_size:] = admittance
-    boundary_block_cache[boundary_cache_key] = block
-    return block
-
-
-def _modal_q_coth(q_values: np.ndarray, thickness: float) -> np.ndarray:
-    """Return modal ``q / tanh(q * thickness)`` with a small-argument limit."""
-
-    argument = q_values * thickness
-    values = np.empty_like(q_values, dtype=complex)
-    small = np.abs(argument) < 1e-8
-    values[small] = (1.0 / thickness) + (q_values[small] ** 2 * thickness / 3.0)
-    values[~small] = q_values[~small] / np.tanh(argument[~small])
-    return values
-
-
-def _modal_q_csch(q_values: np.ndarray, thickness: float) -> np.ndarray:
-    """Return modal ``q / sinh(q * thickness)`` with a small-argument limit."""
-
-    argument = q_values * thickness
-    values = np.empty_like(q_values, dtype=complex)
-    small = np.abs(argument) < 1e-8
-    values[small] = (1.0 / thickness) - (q_values[small] ** 2 * thickness / 6.0)
-    values[~small] = q_values[~small] / np.sinh(argument[~small])
-    return values
-
-
-def _modal_function_matrix(
-    eigenvectors: np.ndarray,
-    modal_values: np.ndarray,
-) -> np.ndarray:
-    """Return ``V @ diag(modal_values) @ V^-1`` without forming ``V^-1``."""
-
-    left_factor = eigenvectors * modal_values[np.newaxis, :]
-    result = np.linalg.solve(eigenvectors.T, left_factor.T).T
-    if np.any(np.isnan(result)) or np.any(np.isinf(result)):
-        raise ValueError("Modal layer function produced NaN/Inf values")
-    return result
-
-
-def _modal_function_matrices(
-    eigenvectors: np.ndarray,
-    first_modal_values: np.ndarray,
-    second_modal_values: np.ndarray,
-) -> tuple[np.ndarray, np.ndarray]:
-    """Return two ``V @ diag(m) @ V^-1`` matrices from one shared solve."""
-
-    first_left_factor = eigenvectors * first_modal_values[np.newaxis, :]
-    second_left_factor = eigenvectors * second_modal_values[np.newaxis, :]
-    stacked_rhs = np.hstack((first_left_factor.T, second_left_factor.T))
-    solved = np.linalg.solve(eigenvectors.T, stacked_rhs)
-    split_index = eigenvectors.shape[0]
-    first_result = solved[:, :split_index].T
-    second_result = solved[:, split_index:].T
-    if (
-        np.any(np.isnan(first_result))
-        or np.any(np.isinf(first_result))
-        or np.any(np.isnan(second_result))
-        or np.any(np.isinf(second_result))
-    ):
-        raise ValueError("Modal layer function produced NaN/Inf values")
-    return first_result, second_result
-
-
-def _cascade_boundary_pair(
-    left: np.ndarray,
-    right: np.ndarray,
-    basis_size: int,
-    *,
-    _profiler: SolverProfiler | None = None,
-) -> np.ndarray:
-    """Cascade two adjacent interface-response blocks into one block."""
-
-    if _profiler is not None:
-        _profiler.add_detail_count("layer_cascade_pair_calls", 1)
-    with _profiler.record("layer_block_cascade_pair") if _profiler is not None else _nullcontext():
-        with _profiler.record("layer_cascade_pair_partition") if _profiler is not None else _nullcontext():
-            l11 = left[:basis_size, :basis_size]
-            l12 = left[:basis_size, basis_size:]
-            l21 = left[basis_size:, :basis_size]
-            l22 = left[basis_size:, basis_size:]
-            r11 = right[:basis_size, :basis_size]
-            r12 = right[:basis_size, basis_size:]
-            r21 = right[basis_size:, :basis_size]
-            r22 = right[basis_size:, basis_size:]
-
-        with _profiler.record("layer_cascade_pair_matrix_setup") if _profiler is not None else _nullcontext():
-            matrix_to_solve = l22 - r11
-            rhs = np.empty((basis_size, 2 * basis_size), dtype=left.dtype)
-            rhs[:, :basis_size] = l21
-            rhs[:, basis_size:] = r12
-        logger.debug("  _cascade_boundary_pair: solving interface system...")
-        if logger.isEnabledFor(logging.DEBUG):
-            try:
-                cond = np.linalg.cond(matrix_to_solve)
-                if cond > 1e12:
-                    logger.warning(f"  interface matrix is nearly singular (cond={cond:.2e})")
-            except Exception:
-                pass
-
-        try:
-            with _profiler.record("layer_cascade_pair_solve") if _profiler is not None else _nullcontext():
-                solved_blocks = np.linalg.solve(matrix_to_solve, rhs)
-        except np.linalg.LinAlgError as e:
-            logger.error(f"  np.linalg.solve failed in cascade: {e}")
-            raise
-
-        solved_l21 = solved_blocks[:, :basis_size]
-        solved_r12 = solved_blocks[:, basis_size:]
-
-        with _profiler.record("layer_cascade_pair_multiply") if _profiler is not None else _nullcontext():
-            top_left = l11 - (l12 @ solved_l21)
-            top_right = l12 @ solved_r12
-            bottom_left = -(r21 @ solved_l21)
-            bottom_right = r22 + (r21 @ solved_r12)
-
-        with _profiler.record("layer_cascade_pair_assemble") if _profiler is not None else _nullcontext():
-            result = np.empty_like(left)
-            result[:basis_size, :basis_size] = top_left
-            result[:basis_size, basis_size:] = top_right
-            result[basis_size:, :basis_size] = bottom_left
-            result[basis_size:, basis_size:] = bottom_right
-
-            if np.any(np.isnan(result)) or np.any(np.isinf(result)):
-                logger.warning("  cascade produced NaN/Inf values")
-
-    return result
-
-
-def _cascade_layer_boundary_blocks(
-    layer_blocks: list[np.ndarray],
-    basis_size: int,
-    *,
-    _profiler: SolverProfiler | None = None,
-) -> np.ndarray | None:
-    """Return the global interface-response block for all finite layers."""
-
-    if not layer_blocks:
-        return None
-    stack_boundary = layer_blocks[0]
-    with _profiler.record("layer_propagation_cascade") if _profiler is not None else _nullcontext():
-        for block in layer_blocks[1:]:
-            stack_boundary = _cascade_boundary_pair(
-                stack_boundary,
-                block,
-                basis_size,
-                _profiler=_profiler,
-            )
-    return stack_boundary
-
-
-def _top_admittance_from_boundary_block(
-    *,
-    stack_boundary: np.ndarray | None,
-    derivative_bottom: np.ndarray,
-) -> np.ndarray:
-    """Return the top admittance implied by the cascaded layer-response block."""
-
-    if stack_boundary is None:
-        return derivative_bottom
-
-    basis_size = derivative_bottom.shape[0]
-    s11 = stack_boundary[:basis_size, :basis_size]
-    s12 = stack_boundary[:basis_size, basis_size:]
-    s21 = stack_boundary[basis_size:, :basis_size]
-    s22 = stack_boundary[basis_size:, basis_size:]
-    bottom_response = np.linalg.solve(derivative_bottom - s22, s21)
-    return s11 + s12 @ bottom_response
-
-
-def _bottom_field_from_boundary_block(
-    *,
-    top_field: np.ndarray,
-    stack_boundary: np.ndarray | None,
-    derivative_bottom: np.ndarray,
-    _profiler: SolverProfiler | None = None,
-) -> np.ndarray:
-    """Return the substrate field for a boundary-block-cascaded stack."""
-
-    if stack_boundary is None:
-        return top_field
-
-    basis_size = top_field.size
-    s21 = stack_boundary[basis_size:, :basis_size]
-    s22 = stack_boundary[basis_size:, basis_size:]
-    with _profiler.record("matrix_solves") if _profiler is not None else _nullcontext():
-        return np.linalg.solve(derivative_bottom - s22, s21 @ top_field)
-
-
-def _angles_from_kx(kx: np.ndarray, k0: float, refractive_index: complex) -> np.ndarray:
-    if abs(np.imag(refractive_index)) > 1e-12:
-        n_for_angles = np.real(refractive_index)
-    else:
-        n_for_angles = float(np.real(refractive_index))
-    ratio = np.real(kx / (k0 * n_for_angles))
-    ratio = np.clip(ratio, -1.0, 1.0)
-    return np.degrees(np.arcsin(ratio))
-
-
-def _kz_branch(value: complex) -> complex:
-    """Select correct branch for sqrt when computing kz.
-    
-    Uses Petit cutoff for branch selection, matching MATLAB's retsqrt(x,0) behavior.
-    
-    Args:
-        value: Complex value to compute sqrt of.
-    
-    Returns:
-        kz with correct branch selected: imag(kz) > 0, or (imag(kz) == 0 and real(kz) >= 0).
-    """
-    kz = np.sqrt(value + 0j)
-    
-    # Petit cutoff: keep if imag > 0, or if (imag == 0 and real >= 0)
-    # Otherwise flip sign
-    if kz.imag < 0 or (np.abs(kz.imag) < 1e-15 and kz.real < 0):
-        kz = -kz
-    
-    return kz
-
-
-def _kz_branch_array(values: np.ndarray) -> np.ndarray:
-    """Select the outgoing/decaying sqrt branch for an array of kz values."""
-
-    kz = np.sqrt(np.asarray(values, dtype=complex) + 0j)
-    flip_mask = (np.imag(kz) < 0) | ((np.abs(np.imag(kz)) < 1e-15) & (np.real(kz) < 0))
-    kz[flip_mask] = -kz[flip_mask]
-    return kz
-
-
-def safe_linalg_solve(A: np.ndarray, b: np.ndarray, context: str = "") -> np.ndarray:
-    """Solve linear system with error handling and logging.
-    
-    Args:
-        A: Coefficient matrix.
-        b: Right-hand side vector or matrix.
-        context: Context string for logging.
-        
-    Returns:
-        Solution vector/matrix.
-        
-    Raises:
-        np.linalg.LinAlgError: If the system cannot be solved.
-    """
-    try:
-        cond = np.linalg.cond(A)
-        if cond > 1e10:
-            logger.warning(f"Matrix condition number is high ({cond:.2e}) in {context}")
-        if cond > 1e15:
-            logger.error(f"Matrix is nearly singular ({cond:.2e}) in {context}")
-    except Exception:
-        pass
-    
-    try:
-        result = np.linalg.solve(A, b)
-        if np.any(np.isnan(result)) or np.any(np.isinf(result)):
-            logger.error(f"Solution contains NaN/Inf in {context}")
-        return result
-    except np.linalg.LinAlgError as e:
-        logger.error(f"Linear solve failed in {context}: {e}")
-        raise
+__all__ = [
+    "ArrayLike",
+    "BoundaryBlockCache",
+    "DiffractionResult",
+    "EigenCache",
+    "FourierBackend",
+    "FourierBackendName",
+    "LayerFieldOperators",
+    "NeviereOptions",
+    "Parameters",
+    "Res1Parameters",
+    "Res1Result",
+    "Res2Parameters",
+    "Res2Result",
+    "Texture1D",
+    "apply_debye_waller_roughness",
+    "debye_waller_roughness_diagnostics",
+    "incidence_sine_from_beta0",
+    "layer_field_operators",
+    "res0",
+    "res1",
+    "res2",
+    "res2_dm",
+    "safe_linalg_solve",
+]
diff --git a/src/grax/simulation/__init__.py b/src/grax/simulation/__init__.py
index 7c4372c..aa6c348 100644
--- a/src/grax/simulation/__init__.py
+++ b/src/grax/simulation/__init__.py
@@ -22,7 +22,7 @@
     multilayer_theta_search_cases,
 )
 from .core import (
-    RCWASimulation,
+    GratingSimulation,
     efficiency_for_order,
     load_experimental_csv,
     plot_order_subset,
@@ -111,7 +111,7 @@ def _calibrate_auto_max_workers_from_result(*, pending_case_count, available_mem
     "BatchSimulationResult",
     "CaseExecutionResult",
     "MultilayerThetaSearchSweepResult",
-    "RCWASimulation",
+    "GratingSimulation",
     "SimulationResult",
     "SingleSimulationResult",
     "ThetaSearchDiagnostics",
diff --git a/src/grax/simulation/batch.py b/src/grax/simulation/batch.py
index 327c3cc..89a382b 100644
--- a/src/grax/simulation/batch.py
+++ b/src/grax/simulation/batch.py
@@ -23,6 +23,8 @@
 from ..gratings import BaseGrating
 from .core import (
     _clone_grating_with_overrides,
+    _validate_solver,
+    normalize_polarization,
     _refresh_interactive_figure,
     _warn_if_numpy_backend_requested,
     efficiency_for_order,
@@ -71,13 +73,50 @@ def _case_memory_mode(case: dict[str, object]) -> str:
     return memory_mode
 
 
+def runner_settings(**overrides: object) -> dict[str, object]:
+    """Return the settings mapping consumed by :func:`_case_payload`.
+
+    Both :class:`BatchSimulationRunner` and the multilayer theta-search sweep
+    need one of these. They used to build it independently, which is how
+    ``solver`` reached the plain-case payload but not the theta-search one: a
+    setting was added to one construction site and silently missed by the other.
+    Defining the keys once means a missing key now raises here instead of
+    quietly falling back to a different solver.
+
+    Args:
+        **overrides: Settings to replace. Unknown names are rejected so a typo
+            cannot silently leave a default in place.
+
+    Returns:
+        Complete runner settings.
+    """
+
+    settings: dict[str, object] = {
+        "diffraction_order": 1,
+        "fourier_orders": 25,
+        "max_fourier_orders": 100,
+        "validate_physical_results": True,
+        "max_reflected_efficiency": 1.05,
+        "min_reflected_efficiency": -1e-8,
+        "backend": "numba",
+        "polarization": "s",
+        "solver": "rcwa",
+        "solver_options": None,
+    }
+    unknown = sorted(set(overrides) - set(settings))
+    if unknown:
+        raise ValueError(f"Unknown runner settings: {unknown}")
+    settings.update(overrides)
+    return settings
+
+
 def _case_payload(case: dict[str, object], runner_settings: dict[str, object]) -> dict[str, object]:
     """Build the serializable payload used by inline and subprocess execution."""
 
     grating = case["grating"]
     if not isinstance(grating, BaseGrating):
         raise TypeError("Each case must provide a 'grating' derived from BaseGrating.")
-    fourier_orders = int(case.get("fourier_orders", runner_settings["default_fourier_orders"]))
+    fourier_orders = int(case.get("fourier_orders", runner_settings["fourier_orders"]))
     max_fourier_orders = int(runner_settings["max_fourier_orders"])
     if fourier_orders > max_fourier_orders:
         logger.warning(
@@ -120,7 +159,7 @@ def _case_payload(case: dict[str, object], runner_settings: dict[str, object]) -
             "workflow": "multilayer_theta_search",
             "grating": grating,
             "energy_ev": float(case["energy_ev"]),
-            "diffraction_order": int(case.get("diffraction_order", runner_settings["default_diffraction_order"])),
+            "diffraction_order": int(case.get("diffraction_order", runner_settings["diffraction_order"])),
             "initial_grazing_angle_deg": case.get("initial_grazing_angle_deg"),
             "multilayer_bragg_order": int(case.get("multilayer_bragg_order", 1)),
             "rough_scan_half_width_deg": float(case.get("rough_scan_half_width_deg", 0.5)),
@@ -141,10 +180,19 @@ def _case_payload(case: dict[str, object], runner_settings: dict[str, object]) -
             "roughness_sigma_nm": case.get("roughness_sigma_nm"),
             "validate_physical_results": bool(runner_settings["validate_physical_results"]),
             "max_reflected_efficiency": float(runner_settings["max_reflected_efficiency"]),
-            "min_efficiency": float(runner_settings["min_reflected_efficiency"]),
+            "min_reflected_efficiency": float(runner_settings["min_reflected_efficiency"]),
             "max_total_reflected_efficiency": _BATCH_MAX_TOTAL_REFLECTED_EFFICIENCY,
             "precise_peak_selection_mode": str(case.get("precise_peak_selection_mode", "max")),
+            "polarization": normalize_polarization(
+                case.get("polarization", runner_settings["polarization"])
+            ),
             "backend": runner_settings["backend"],
+            "solver": _validate_solver(
+                str(case.get("solver", runner_settings["solver"]))
+            ),
+            "solver_options": case.get(
+                "solver_options", runner_settings["solver_options"]
+            ),
         }
 
     return {
@@ -155,15 +203,19 @@ def _case_payload(case: dict[str, object], runner_settings: dict[str, object]) -
         ),
         "energy_ev": float(case["energy_ev"]),
         "grazing_angle_deg": float(case["grazing_angle_deg"]),
-        "diffraction_order": int(case.get("diffraction_order", runner_settings["default_diffraction_order"])),
+        "diffraction_order": int(case.get("diffraction_order", runner_settings["diffraction_order"])),
         "fourier_orders": fourier_orders,
         "_memory_mode": _case_memory_mode(case),
         "profile_memory": bool(case.get("profile_memory", False)),
         "roughness_sigma_nm": case.get("roughness_sigma_nm"),
-        "polarization": str(case.get("polarization", runner_settings["default_polarization"])),
+        "polarization": normalize_polarization(
+            case.get("polarization", runner_settings["polarization"])
+        ),
+        "solver": _validate_solver(str(case.get("solver", runner_settings["solver"]))),
+        "solver_options": case.get("solver_options", runner_settings["solver_options"]),
         "validate_physical_results": bool(runner_settings["validate_physical_results"]),
         "max_reflected_efficiency": float(runner_settings["max_reflected_efficiency"]),
-        "min_efficiency": float(runner_settings["min_reflected_efficiency"]),
+        "min_reflected_efficiency": float(runner_settings["min_reflected_efficiency"]),
         "max_total_reflected_efficiency": _BATCH_MAX_TOTAL_REFLECTED_EFFICIENCY,
         "backend": runner_settings["backend"],
     }
@@ -586,11 +638,16 @@ def _load_checkpoint_case_results(checkpoint_path: Path) -> dict[str, CaseExecut
 
 
 class BatchSimulationRunner:
-    """Stream RCWA simulations for arbitrary case iterables.
+    """Stream grating simulations for arbitrary case iterables.
+
+    Every case inherits the runner's ``diffraction_order``, ``fourier_orders``,
+    ``polarization``, ``solver`` and ``solver_options`` unless it carries its own
+    key of the same name. These mirror the arguments of
+    :func:`grax.run_simulation`.
 
     Args:
-        default_diffraction_order: Default selected diffraction order.
-        default_fourier_orders: Default Fourier truncation order.
+        diffraction_order: Selected diffraction order for cases without their own.
+        fourier_orders: Fourier truncation order for cases without their own.
         max_fourier_orders: Maximum allowed Fourier orders.
         backend: Fourier coefficient backend selector. ``"numba"`` is the
             default backend. ``"numpy"`` remains available temporarily for
@@ -635,8 +692,8 @@ class BatchSimulationRunner:
     def __init__(
         self,
         *,
-        default_diffraction_order: int = 1,
-        default_fourier_orders: int = 25,
+        diffraction_order: int = 1,
+        fourier_orders: int = 25,
         execution_mode: ExecutionMode = "inline",
         max_workers: MaxWorkers = None,
         timeout: float = 3600,
@@ -659,18 +716,20 @@ def __init__(
         retry_selected_efficiency_threshold: float = 1e-4,
         max_zero_efficiency_retries: int = 3,
         backend: str = "numba",
-        default_polarization: str = "s",
+        polarization: str = "s",
+        solver: str = "rcwa",
+        solver_options: object | None = None,
     ) -> None:
         """Initialize a streaming batch simulation runner.
 
-        Configures batch execution parameters for RCWA simulations. Supports inline
+        Configures batch execution parameters. Supports inline
         single-threaded execution and multiprocessing via subprocess workers with
         automatic memory calibration.
 
         Args:
-            default_diffraction_order: Default diffraction order for efficiency selection
+            diffraction_order: Default diffraction order for efficiency selection
                 when case does not specify. Must be positive integer.
-            default_fourier_orders: Default Fourier truncation orders when case does
+            fourier_orders: Default Fourier truncation orders when case does
                 not specify. Higher values improve accuracy but increase computation.
             execution_mode: Execution strategy. ``inline`` runs in current process,
                 ``subprocess`` spawns separate worker processes.
@@ -714,13 +773,19 @@ def __init__(
                 default backend. ``"numpy"`` remains available temporarily for
                 compatibility but is deprecated and will be removed in a future
                 version.
-            default_polarization: Default polarization used when a case omits the
-                value. Must be ``"s"`` or ``"p"``.
+            polarization: Incident polarization for every case that does not
+                carry its own ``"polarization"`` key. Must be ``"s"`` or ``"p"``.
+            solver: Electromagnetic solver for every case that does not carry its
+                own ``"solver"`` key. ``"rcwa"`` (default) or ``"neviere"``.
+            solver_options: Solver settings for every case that does not carry
+                its own ``"solver_options"`` key, as a
+                :class:`grax.NeviereOptions` or an equivalent mapping. Ignored by
+                the RCWA solver.
 
         Example:
             >>> runner = BatchSimulationRunner(
-            ...     default_diffraction_order=1,
-            ...     default_fourier_orders=25,
+            ...     diffraction_order=1,
+            ...     fourier_orders=25,
             ...     max_workers="auto",
             ...     checkpoint_dir="results",
             ...     resume=True
@@ -744,8 +809,8 @@ def __init__(
                 "resume=True requires checkpoint_dir to be specified. "
                 "Please provide a checkpoint_dir path to enable resumption from checkpoint."
             )
-        self.default_diffraction_order = default_diffraction_order
-        self.default_fourier_orders = default_fourier_orders
+        self.diffraction_order = diffraction_order
+        self.fourier_orders = fourier_orders
         self.execution_mode = execution_mode
         self.max_workers = max_workers
         self.resolved_max_workers = resolved_max_workers
@@ -769,9 +834,9 @@ def __init__(
         self.retry_selected_efficiency_threshold = float(retry_selected_efficiency_threshold)
         self.max_zero_efficiency_retries = max(0, int(max_zero_efficiency_retries))
         self.backend = backend
-        self.default_polarization = default_polarization
-        if self.default_polarization not in {"s", "p"}:
-            raise ValueError("default_polarization must be 's' or 'p'.")
+        self.polarization = normalize_polarization(polarization)
+        self.solver = _validate_solver(solver)
+        self.solver_options = solver_options
         self._live_figure: plt.Figure | None = None
         self._live_axis: plt.Axes | None = None
         self._live_x_values: list[float] = []
@@ -799,7 +864,7 @@ def run_cases(
     ) -> Iterator[CaseExecutionResult]:
         """Yield simulation results for an arbitrary iterable of cases.
 
-        Executes RCWA simulations for all provided cases with support for
+        Executes simulations for all provided cases with support for
         single-threaded inline execution or multiprocessing via subprocess workers,
         real-time progress bars and live plotting, checkpoint persistence and
         resume capability, automatic worker calibration for memory-efficient
@@ -855,7 +920,11 @@ def run_cases(
             pending_cases = self._prepare_pending_cases(iterable, completed_ids)
             effective_total_cases = len(completed_ids) + len(pending_cases) if self.resume else len(pending_cases)
             if self.show_progress:
-                progress = _simulation_api().tqdm(total=effective_total_cases, desc="RCWA batch", unit="case")
+                progress = _simulation_api().tqdm(
+                    total=effective_total_cases,
+                    desc=f"{self.solver} batch",
+                    unit="case",
+                )
                 if self.resume and completed_ids:
                     progress.update(len(completed_ids))
             calibrated_result = None
@@ -911,22 +980,24 @@ def _settings(self) -> dict[str, object]:
         and validation.
 
         Returns:
-            Dictionary with settings for: default_diffraction_order,
-            default_fourier_orders, max_fourier_orders, validate_physical_results,
+            Dictionary with settings for: diffraction_order,
+            fourier_orders, max_fourier_orders, validate_physical_results,
             max_reflected_efficiency, min_reflected_efficiency,
             backend.
         """
 
-        return {
-            "default_diffraction_order": self.default_diffraction_order,
-            "default_fourier_orders": self.default_fourier_orders,
-            "max_fourier_orders": self.max_fourier_orders,
-            "validate_physical_results": self.validate_physical_results,
-            "max_reflected_efficiency": self.max_reflected_efficiency,
-            "min_reflected_efficiency": self.min_reflected_efficiency,
-            "backend": self.backend,
-            "default_polarization": self.default_polarization,
-        }
+        return runner_settings(
+            diffraction_order=self.diffraction_order,
+            fourier_orders=self.fourier_orders,
+            max_fourier_orders=self.max_fourier_orders,
+            validate_physical_results=self.validate_physical_results,
+            max_reflected_efficiency=self.max_reflected_efficiency,
+            min_reflected_efficiency=self.min_reflected_efficiency,
+            backend=self.backend,
+            polarization=self.polarization,
+            solver=self.solver,
+            solver_options=self.solver_options,
+        )
 
     def _prepare_pending_cases(
         self,
@@ -1080,6 +1151,8 @@ def submit_next_case() -> bool:
                                 status="ok",
                                 case_data=case_data,
                                 polarization=single.polarization,
+                                solver=single.solver,
+                                solver_options=single.solver_options,
                                 theta_search_diagnostics=single.theta_search_diagnostics,
                                 retry_triggered=single.retry_triggered,
                                 retry_attempts=single.retry_attempts,
@@ -1110,7 +1183,8 @@ def submit_next_case() -> bool:
                                 status="error",
                                 error_message=str(message["error"]),
                                 case_data=case_data,
-                                polarization=str(case.get("polarization", self.default_polarization)),
+                                polarization=str(case.get("polarization", self.polarization)),
+                                solver=str(case.get("solver", self.solver)),
                                 peak_memory_bytes=None,
                                 wall_seconds=None,
                             )
@@ -1237,6 +1311,8 @@ def _execute_case(
                 status="ok",
                 case_data=case_data,
                 polarization=single.polarization,
+                solver=single.solver,
+                solver_options=single.solver_options,
                 theta_search_diagnostics=single.theta_search_diagnostics,
                 retry_triggered=single.retry_triggered,
                 retry_attempts=single.retry_attempts,
@@ -1263,7 +1339,8 @@ def _execute_case(
                 status="error",
                 error_message=str(error),
                 case_data=case_data,
-                polarization=str(case.get("polarization", self.default_polarization)),
+                polarization=str(case.get("polarization", self.polarization)),
+                solver=str(case.get("solver", self.solver)),
                 peak_memory_bytes=None,
                 wall_seconds=None,
             )
@@ -1319,8 +1396,8 @@ def _write_metadata(self, metadata: dict[str, object]) -> None:
                 "execution_mode": self.execution_mode,
                 "max_workers": self.max_workers,
                 "resolved_max_workers": self.resolved_max_workers,
-                "default_diffraction_order": self.default_diffraction_order,
-                "default_fourier_orders": self.default_fourier_orders,
+                "diffraction_order": self.diffraction_order,
+                "fourier_orders": self.fourier_orders,
             }
         )
         with (self.checkpoint_dir / "metadata.json").open("w", encoding="utf-8") as handle:
diff --git a/src/grax/simulation/cases.py b/src/grax/simulation/cases.py
index f0e903a..340b372 100644
--- a/src/grax/simulation/cases.py
+++ b/src/grax/simulation/cases.py
@@ -34,7 +34,7 @@ def fixed_angle_cases(
         energies_ev: Iterable of photon energies in electronvolts.
         grazing_angle_deg: Grazing incidence angle in degrees.
         polarization: Incident polarization, ``"s"`` or ``"p"``. When ``None``
-            the runner's ``default_polarization`` is used.
+            the runner's ``polarization`` is used.
 
     Yields:
         Case dictionaries suitable for :class:`BatchSimulationRunner`.
@@ -186,6 +186,7 @@ def multilayer_theta_search_cases(
     multilayer_bragg_order: int = 1,
     roughness_sigma_nm: float | None = None,
     precise_peak_selection_mode: PeakSelectionMode = "max",
+    polarization: str | None = None,
 ) -> Iterator[dict[str, object]]:
     """Yield energy-only cases for the multilayer theta-search workflow.
 
@@ -216,6 +217,8 @@ def multilayer_theta_search_cases(
         final_z_resolution_nm: Z resolution used during the final solve.
         multilayer_bragg_order: Positive Bragg order used for the analytical estimate.
         roughness_sigma_nm: Optional rms roughness in nanometers.
+        polarization: Incident polarization, ``"s"``/``"TE"`` or ``"p"``/``"TM"``.
+            When ``None`` the runner's ``polarization`` is used.
         precise_peak_selection_mode: Mode used to select the final theta from the
             precise scan. ``"max"`` uses the sampled maximum, ``"gauss"`` fits a
             local Gaussian, and ``"voigt"`` fits a local Voigt profile.
@@ -253,6 +256,7 @@ def multilayer_theta_search_cases(
             "multilayer_bragg_order": multilayer_bragg_order,
             "roughness_sigma_nm": roughness_sigma_nm,
             "precise_peak_selection_mode": precise_peak_selection_mode,
+            **({} if polarization is None else {"polarization": polarization}),
             "case_id": f"{_THETA_SEARCH_CASE_ID_PREFIX}-{index:08d}",
             "grating": grating,
             "energy_ev": float(energy_ev),
diff --git a/src/grax/simulation/core.py b/src/grax/simulation/core.py
index 9d1845e..0da4c08 100644
--- a/src/grax/simulation/core.py
+++ b/src/grax/simulation/core.py
@@ -19,7 +19,8 @@
 import numpy as np
 
 from ..gratings import BaseGrating
-from ..rcwa_1d import res0, res1, res2
+from ..solvers import res0, res1, res2, res2_dm
+from ..solvers.neviere import NeviereOptions, build_grating_epsilon_sampler, coerce_neviere_options
 from ._memory import PeakMemorySampler, format_memory_mb
 from ._profiling import SolverProfiler
 from .models import (
@@ -36,6 +37,65 @@
 # count, and the solver hard-caps at 100 orders (201 modes) regardless.
 _SUPERCELL_FOURIER_ORDER_WARNING_THRESHOLD = 40
 
+#: Electromagnetic solvers selectable through ``solver=``.
+SOLVER_NAMES = ("rcwa", "neviere")
+
+
+def _validate_solver(solver: str) -> str:
+    """Return the validated solver name."""
+
+    if solver not in SOLVER_NAMES:
+        raise ValueError(f"solver must be one of {SOLVER_NAMES}, got {solver!r}.")
+    return solver
+
+
+#: Accepted polarization spellings and the canonical value each maps to.
+#:
+#: ``"te"`` and ``"tm"`` are the names used throughout the grating-theory
+#: literature this solver follows, and by the solver internals themselves
+#: (``res0``, ``_solve_te_stack``); ``"s"`` and ``"p"`` are what the public API
+#: has always taken. They are the same two states.
+POLARIZATION_ALIASES = {"s": "s", "te": "s", "p": "p", "tm": "p"}
+
+#: Canonical polarization values. Everything downstream sees only these.
+POLARIZATION_NAMES = ("s", "p")
+
+
+def normalize_polarization(value: str) -> str:
+    """Return the canonical ``"s"`` or ``"p"`` for one polarization name.
+
+    Accepts ``"s"``, ``"p"``, ``"TE"`` and ``"TM"``, case-insensitively and
+    ignoring surrounding whitespace. The canonical value is always ``"s"`` or
+    ``"p"``, so passing ``"TE"`` gives back ``"s"``: results, CSV columns and
+    checkpoints only ever carry the two canonical spellings, and nothing
+    downstream has to know about the aliases.
+
+    Note:
+        ``s`` and ``TE`` name the same state only in **classical mounting**,
+        where the plane of incidence is perpendicular to the grooves. There, TE
+        has the electric field along the grooves, which is also the direction
+        perpendicular to the plane of incidence, so the two definitions coincide.
+        In a conical mounting they do not: ``s``/``p`` are defined against the
+        plane of incidence and ``TE``/``TM`` against the groove direction. This
+        solver is one-dimensional and classical only, so the alias is exact here
+        -- but it would stop being exact if conical mounting were ever added.
+
+    Args:
+        value: Polarization name in any accepted spelling.
+
+    Returns:
+        ``"s"`` or ``"p"``.
+
+    Raises:
+        ValueError: If the name is not one of the accepted spellings.
+    """
+
+    normalized = POLARIZATION_ALIASES.get(str(value).strip().lower())
+    if normalized is None:
+        accepted = ", ".join(repr(name) for name in POLARIZATION_ALIASES)
+        raise ValueError(f"polarization must be one of {accepted}, got {value!r}.")
+    return normalized
+
 
 def _warn_if_numpy_backend_requested(backend: str, *, stacklevel: int = 3) -> None:
     """Warn when callers explicitly request the deprecated NumPy backend."""
@@ -95,7 +155,7 @@ def _validate_reflected_efficiencies(
     period_nm: float,
     orders: np.ndarray,
     efficiency_all: np.ndarray,
-    min_efficiency: float,
+    min_reflected_efficiency: float,
     max_reflected_efficiency: float,
     max_total_reflected_efficiency: float,
 ) -> None:
@@ -107,14 +167,14 @@ def _validate_reflected_efficiencies(
         period_nm: Grating period in nanometers.
         orders: Calculated diffraction orders.
         efficiency_all: Reflected efficiency for all orders.
-        min_efficiency: Minimum accepted efficiency value.
+        min_reflected_efficiency: Minimum accepted efficiency value.
         max_reflected_efficiency: Maximum accepted single-order efficiency.
         max_total_reflected_efficiency: Maximum accepted propagating reflected sum.
     """
 
     minimum_efficiency = float(np.min(efficiency_all))
     maximum_efficiency = float(np.max(efficiency_all))
-    if minimum_efficiency < min_efficiency:
+    if minimum_efficiency < min_reflected_efficiency:
         raise ValueError(
             "Non-physical negative diffraction efficiency detected at "
             f"{photon_energy_ev:.6g} eV: min={minimum_efficiency:.6g}"
@@ -167,7 +227,7 @@ def _run_single_realization(
     *,
     energy_ev: float,
     grazing_angle_deg: float,
-    polarization: Literal["s", "p"],
+    polarization: str,
     effective_roughness_sigma_nm: float | None,
     num_supercells: int,
     effective_period_nm: float,
@@ -175,8 +235,10 @@ def _run_single_realization(
     _memory_mode: Literal["legacy_dense", "low_memory"],
     _profiler: SolverProfiler | None,
     backend: str,
+    solver: str,
+    solver_options: NeviereOptions,
 ) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
-    """Run one full RCWA solve and return raw (orders, efficiency_all, diffraction_angle_all).
+    """Run one full solve and return raw (orders, efficiency_all, diffraction_angle_all).
 
     One "realization" is one concrete roughness draw (or the single
     deterministic solve when there's no roughness/Debye-Waller roughness).
@@ -203,13 +265,33 @@ def _run_single_realization(
         _profiler=_profiler,
         _fourier_backend=backend,
     )
-    ef = res2(
-        aa,
-        profile,
-        parm,
-        roughness_sigma_nm=effective_roughness_sigma_nm,
-        _profiler=_profiler,
-    )
+    if solver == "neviere":
+        epsilon_sampler = None
+        if solver_options.z_sampling == "continuous":
+            epsilon_sampler = build_grating_epsilon_sampler(
+                grating,
+                photon_energy_ev=float(energy_ev),
+                period_nm=effective_period_nm,
+                orders=aa.orders,
+                fourier_backend=backend,
+            )
+        ef = res2_dm(
+            aa,
+            profile,
+            parm,
+            roughness_sigma_nm=effective_roughness_sigma_nm,
+            options=solver_options,
+            epsilon_sampler=epsilon_sampler,
+            _profiler=_profiler,
+        )
+    else:
+        ef = res2(
+            aa,
+            profile,
+            parm,
+            roughness_sigma_nm=effective_roughness_sigma_nm,
+            _profiler=_profiler,
+        )
 
     with _profiler.record("postprocessing") if _profiler is not None else _nullcontext():
         orders = np.asarray(ef.inc_top_reflected.order, dtype=float) / float(num_supercells)
@@ -229,16 +311,18 @@ def run_simulation(
     diffraction_order: int = 1,
     fourier_orders: int = 25,
     roughness_sigma_nm: float | None = None,
-    polarization: Literal["s", "p"] = "s",
+    polarization: str = "s",
     validate_physical_results: bool = True,
     max_reflected_efficiency: float = 1.05,
-    min_efficiency: float = -1e-8,
+    min_reflected_efficiency: float = -1e-8,
     max_total_reflected_efficiency: float = 1.05,
     _memory_mode: Literal["legacy_dense", "low_memory"] = "low_memory",
     _profiler: SolverProfiler | None = None,
     backend: str = "numba",
+    solver: Literal["rcwa", "neviere"] = "rcwa",
+    solver_options: NeviereOptions | dict[str, object] | None = None,
 ) -> SingleSimulationResult:
-    """Run one RCWA simulation case and return a typed result.
+    """Run one simulation case and return a typed result.
 
     Args:
         grating: Grating profile and material stack.
@@ -251,7 +335,7 @@ def run_simulation(
             ``"p"`` selects TM.
         validate_physical_results: Whether to validate reflected efficiencies.
         max_reflected_efficiency: Maximum allowed single-order reflected efficiency.
-        min_efficiency: Minimum allowed efficiency.
+        min_reflected_efficiency: Minimum allowed efficiency.
         max_total_reflected_efficiency: Maximum allowed sum of propagating reflected efficiencies.
         _memory_mode: Internal texture-generation mode. ``"low_memory"`` is the
             public path. ``"legacy_dense"`` keeps the older dense-grid path
@@ -260,9 +344,17 @@ def run_simulation(
             default backend. ``"numpy"`` remains available temporarily for
             compatibility but is deprecated and will be removed in a future
             version.
+        solver: Electromagnetic solver. ``"rcwa"`` (default) eigen-decomposes
+            each layer; ``"neviere"`` integrates the coupled first-order system
+            in ``z`` with the Nevière differential method. Both use the same
+            Fourier operators and the same efficiency extraction, so they are
+            directly comparable.
+        solver_options: Integration settings for ``solver="neviere"``, as a
+            :class:`grax.NeviereOptions` or an equivalent mapping. Ignored by
+            the RCWA solver.
 
     Returns:
-        Single-case RCWA result.
+        Single-case simulation result.
     """
 
     if not isinstance(grating, BaseGrating):
@@ -285,14 +377,16 @@ def run_simulation(
             )
         else:
             effective_roughness_sigma_nm = float(grating.roughness.sigma_nm)
-    if polarization not in {"s", "p"}:
-        raise ValueError("polarization must be 's' or 'p'.")
+    polarization = normalize_polarization(polarization)
     if _memory_mode not in {"legacy_dense", "low_memory"}:
         raise ValueError("memory_mode must be 'low_memory' or 'legacy_dense'.")
+    _validate_solver(solver)
+    resolved_solver_options = coerce_neviere_options(solver_options)
     _warn_if_numpy_backend_requested(backend, stacklevel=2)
 
     logger.info(
-        "Running simulation at %.2f eV, grazing=%.3f deg, fourier_orders=%s, memory_mode=%s",
+        "Running %s simulation at %.2f eV, grazing=%.3f deg, fourier_orders=%s, memory_mode=%s",
+        solver,
         energy_ev,
         grazing_angle_deg,
         fourier_orders,
@@ -345,6 +439,8 @@ def run_simulation(
                     _memory_mode=_memory_mode,
                     _profiler=_profiler,
                     backend=backend,
+                    solver=solver,
+                    solver_options=resolved_solver_options,
                 )
                 if orders is None:
                     orders = realization_orders
@@ -366,6 +462,8 @@ def run_simulation(
                 _memory_mode=_memory_mode,
                 _profiler=_profiler,
                 backend=backend,
+                solver=solver,
+                solver_options=resolved_solver_options,
             )
 
         order_index = np.where(np.isclose(orders, -float(diffraction_order)))[0]
@@ -380,7 +478,7 @@ def run_simulation(
                 period_nm=grating.period_nm,
                 orders=orders,
                 efficiency_all=all_efficiency,
-                min_efficiency=min_efficiency,
+                min_reflected_efficiency=min_reflected_efficiency,
                 max_reflected_efficiency=max_reflected_efficiency,
                 max_total_reflected_efficiency=max_total_reflected_efficiency,
             )
@@ -402,6 +500,10 @@ def run_simulation(
             num_supercells=num_supercells,
             num_realizations=num_realizations,
             polarization=polarization,
+            solver=solver,
+            solver_options=(
+                resolved_solver_options.to_dict() if solver == "neviere" else None
+            ),
         )
 
     _log_simulation_memory_usage(
@@ -621,8 +723,13 @@ def plot_order_subset(
     plt.close(figure)
 
 
-class RCWASimulation:
-    """Compatibility wrapper around :func:`run_simulation` for internal tests."""
+class GratingSimulation:
+    """Object-style wrapper around :func:`run_simulation`.
+
+    Drives whichever solver ``solver=`` selects. Named ``RCWASimulation``
+    until a second solver existed, at which point the old name described only
+    one of the two things it can do.
+    """
 
     def __init__(
         self,
@@ -631,17 +738,20 @@ def __init__(
         diffraction_order: int = 1,
         fourier_orders: int = 25,
         grazing_angle_deg: float = 4.0,
-        polarization: Literal["s", "p"] = "s",
+        polarization: str = "s",
         live_plot: bool = False,
         validate_physical_results: bool = True,
         max_reflected_efficiency: float = 1.05,
-        min_efficiency: float = -1e-8,
+        min_reflected_efficiency: float = -1e-8,
         max_total_reflected_efficiency: float = 1.05,
         roughness_sigma_nm: float | None = None,
         backend: str = "numba",
+        solver: Literal["rcwa", "neviere"] = "rcwa",
+        solver_options: NeviereOptions | dict[str, object] | None = None,
     ) -> None:
         """Initialize a compatibility simulation object."""
 
+        _validate_solver(solver)
         _warn_if_numpy_backend_requested(backend, stacklevel=2)
         self.grating = grating
         self.diffraction_order = diffraction_order
@@ -651,10 +761,12 @@ def __init__(
         self.live_plot = live_plot
         self.validate_physical_results = validate_physical_results
         self.max_reflected_efficiency = max_reflected_efficiency
-        self.min_efficiency = min_efficiency
+        self.min_reflected_efficiency = min_reflected_efficiency
         self.max_total_reflected_efficiency = max_total_reflected_efficiency
         self.roughness_sigma_nm = roughness_sigma_nm
         self.backend = backend
+        self.solver = solver
+        self.solver_options = solver_options
         self._live_comparison_figure = None
         self._live_comparison_axis = None
 
@@ -671,9 +783,11 @@ def run_single(self, photon_energy_ev: float) -> dict[str, float | np.ndarray]:
             roughness_sigma_nm=self.roughness_sigma_nm,
             validate_physical_results=self.validate_physical_results,
             max_reflected_efficiency=self.max_reflected_efficiency,
-            min_efficiency=self.min_efficiency,
+            min_reflected_efficiency=self.min_reflected_efficiency,
             max_total_reflected_efficiency=self.max_total_reflected_efficiency,
             backend=self.backend,
+            solver=self.solver,
+            solver_options=self.solver_options,
         )
         return {
             "orders": result.orders,
@@ -699,9 +813,11 @@ def run(self, photon_energy_ev: float | list[float] | np.ndarray) -> SimulationR
                 roughness_sigma_nm=self.roughness_sigma_nm,
                 validate_physical_results=self.validate_physical_results,
                 max_reflected_efficiency=self.max_reflected_efficiency,
-                min_efficiency=self.min_efficiency,
+                min_reflected_efficiency=self.min_reflected_efficiency,
                 max_total_reflected_efficiency=self.max_total_reflected_efficiency,
                 backend=self.backend,
+                solver=self.solver,
+                solver_options=self.solver_options,
             )
             for energy in energies
         ]
@@ -737,7 +853,7 @@ def _validate_reflected_efficiencies(
             period_nm=self.grating.period_nm,
             orders=orders,
             efficiency_all=efficiency_all,
-            min_efficiency=self.min_efficiency,
+            min_reflected_efficiency=self.min_reflected_efficiency,
             max_reflected_efficiency=self.max_reflected_efficiency,
             max_total_reflected_efficiency=self.max_total_reflected_efficiency,
         )
diff --git a/src/grax/simulation/models.py b/src/grax/simulation/models.py
index 6aebcff..0a8b645 100644
--- a/src/grax/simulation/models.py
+++ b/src/grax/simulation/models.py
@@ -70,7 +70,7 @@ class ThetaSearchDiagnostics:
 
 @dataclass
 class SingleSimulationResult:
-    """Result for one RCWA simulation case.
+    """Result for one grating simulation case.
 
     Attributes:
         energy_ev: Photon energy in electronvolts.
@@ -92,6 +92,12 @@ class SingleSimulationResult:
             realizations averaged into this result (mirrors
             ``RoughnessSpec.num_realizations``); ``1`` when no averaging was
             in effect (including all Debye-Waller and no-roughness runs).
+        solver: Electromagnetic solver that produced this result, ``"rcwa"`` or
+            ``"neviere"``.
+        solver_options: Solver settings that produced this result, or ``None``
+            when the solver takes none. Recorded so a checkpointed differential-
+            method run is reproducible: the solver name alone does not pin the
+            integration settings.
         theta_search_diagnostics: Optional transient theta-search diagnostics.
         retry_triggered: Whether zero-efficiency retry logic was triggered.
         retry_attempts: Number of additional retry attempts after the first run.
@@ -122,6 +128,8 @@ class SingleSimulationResult:
     num_supercells: int = 1
     num_realizations: int = 1
     polarization: str = "s"
+    solver: str = "rcwa"
+    solver_options: dict[str, object] | None = None
     theta_search_diagnostics: ThetaSearchDiagnostics | None = None
     retry_triggered: bool = False
     retry_attempts: int = 0
@@ -171,6 +179,10 @@ class CaseExecutionResult:
         peak_memory_bytes: Peak tracked memory during execution, when profiling is enabled.
         wall_seconds: Total wall time during execution, when profiling is enabled.
         case_data: Original serializable case metadata without the grating object.
+        solver: Electromagnetic solver that produced this result, ``"rcwa"`` or
+            ``"neviere"``.
+        solver_options: Solver settings that produced this result, or ``None``
+            when the solver takes none.
         theta_search_diagnostics: Optional transient theta-search diagnostics.
         retry_triggered: Whether zero-efficiency retry logic was triggered.
         retry_attempts: Number of additional retry attempts after the first run.
@@ -204,6 +216,8 @@ class CaseExecutionResult:
     wall_seconds: float | None = None
     case_data: dict[str, object] = field(default_factory=dict)
     polarization: str = "s"
+    solver: str = "rcwa"
+    solver_options: dict[str, object] | None = None
     theta_search_diagnostics: ThetaSearchDiagnostics | None = None
     retry_triggered: bool = False
     retry_attempts: int = 0
diff --git a/src/grax/simulation/serialization.py b/src/grax/simulation/serialization.py
index e0d3fc0..1ff19fa 100644
--- a/src/grax/simulation/serialization.py
+++ b/src/grax/simulation/serialization.py
@@ -69,6 +69,8 @@ def _single_result_to_record(result: SingleSimulationResult) -> dict[str, object
         "fourier_orders": result.fourier_orders,
         "roughness_sigma_nm": result.roughness_sigma_nm,
         "polarization": result.polarization,
+        "solver": result.solver,
+        "solver_options": result.solver_options,
         "theta_search_diagnostics": diagnostics_record,
         "retry_triggered": result.retry_triggered,
         "retry_attempts": result.retry_attempts,
@@ -168,6 +170,8 @@ def _single_result_from_record(record: dict[str, object]) -> SingleSimulationRes
             None if record.get("roughness_sigma_nm") is None else float(record["roughness_sigma_nm"])
         ),
         polarization=str(record.get("polarization", "s")),
+        solver=str(record.get("solver", "rcwa")),
+        solver_options=record.get("solver_options"),
         theta_search_diagnostics=diagnostics,
         retry_triggered=bool(record.get("retry_triggered", False)),
         retry_attempts=int(record.get("retry_attempts", 0)),
@@ -257,6 +261,8 @@ def _case_result_to_record(result: CaseExecutionResult) -> dict[str, object]:
         "wall_seconds": result.wall_seconds,
         "case_data": _json_safe_case_data(result.case_data),
         "polarization": result.polarization,
+        "solver": result.solver,
+        "solver_options": result.solver_options,
         "theta_search_diagnostics": diagnostics_record,
         "retry_triggered": result.retry_triggered,
         "retry_attempts": result.retry_attempts,
@@ -362,6 +368,8 @@ def _case_result_from_record(record: dict[str, object]) -> CaseExecutionResult:
         wall_seconds=None if record.get("wall_seconds") is None else float(record["wall_seconds"]),
         case_data=dict(record.get("case_data", {})),
         polarization=str(record.get("polarization", "s")),
+        solver=str(record.get("solver", "rcwa")),
+        solver_options=record.get("solver_options"),
         theta_search_diagnostics=diagnostics,
         retry_triggered=bool(record.get("retry_triggered", False)),
         retry_attempts=int(record.get("retry_attempts", 0)),
diff --git a/src/grax/simulation/theta_search.py b/src/grax/simulation/theta_search.py
index 00ba154..0894bde 100644
--- a/src/grax/simulation/theta_search.py
+++ b/src/grax/simulation/theta_search.py
@@ -165,9 +165,12 @@ def _run_theta_scan(
     roughness_sigma_nm: float | None,
     validate_physical_results: bool,
     max_reflected_efficiency: float,
-    min_efficiency: float,
+    min_reflected_efficiency: float,
     max_total_reflected_efficiency: float,
     backend: str,
+    solver: str,
+    solver_options: object | None,
+    polarization: str,
 ) -> tuple[np.ndarray, list[SingleSimulationResult]]:
     """Run one theta scan and return selected efficiencies plus full results."""
 
@@ -181,9 +184,12 @@ def _run_theta_scan(
             roughness_sigma_nm=roughness_sigma_nm,
             validate_physical_results=validate_physical_results,
             max_reflected_efficiency=max_reflected_efficiency,
-            min_efficiency=min_efficiency,
+            min_reflected_efficiency=min_reflected_efficiency,
             max_total_reflected_efficiency=max_total_reflected_efficiency,
             backend=backend,
+            solver=solver,
+            solver_options=solver_options,
+            polarization=polarization,
         )
         for theta_deg in theta_grid_deg
     ]
@@ -318,10 +324,13 @@ def run_multilayer_theta_search(
     roughness_sigma_nm: float | None = None,
     validate_physical_results: bool = True,
     max_reflected_efficiency: float = 1.05,
-    min_efficiency: float = -1e-8,
+    min_reflected_efficiency: float = -1e-8,
     max_total_reflected_efficiency: float = 1.05,
     precise_peak_selection_mode: PeakSelectionMode = "max",
     backend: str = "numba",
+    solver: str = "rcwa",
+    solver_options: object | None = None,
+    polarization: str = "s",
     diagnostic_callback: Callable[[ThetaSearchDiagnostics, float], None] | None = None,
 ) -> SingleSimulationResult:
     """Run one energy point with an internal rough/precise grazing-angle search.
@@ -375,13 +384,21 @@ def run_multilayer_theta_search(
             reflected efficiency, and maximum total propagating reflected efficiency.
         max_reflected_efficiency: Maximum allowed single-order reflected efficiency
             during validation.
-        min_efficiency: Minimum allowed efficiency (slightly negative values allowed
+        min_reflected_efficiency: Minimum allowed efficiency (slightly negative values allowed
             for numerical noise).
         max_total_reflected_efficiency: Maximum allowed sum of propagating reflected
             efficiencies.
         precise_peak_selection_mode: Mode used to select the final theta from the
             precise scan. ``"max"`` uses the sampled maximum, ``"gauss"`` fits a
             local Gaussian neighborhood, and ``"voigt"`` fits a local Voigt profile.
+        polarization: Incident polarization used for every stage of the search.
+            ``"s"``/``"TE"`` (default) or ``"p"``/``"TM"``.
+        solver: Electromagnetic solver used for every stage of the search.
+            ``"rcwa"`` (default) or ``"neviere"``. All three stages use the same
+            solver so the selected angle and the final efficiency are consistent.
+        solver_options: Integration settings for ``solver="neviere"``, as a
+            :class:`grax.NeviereOptions` or an equivalent mapping. Ignored by the
+            RCWA solver.
         backend: Fourier coefficient backend selector. ``"numba"`` is the
             default backend. ``"numpy"`` remains available temporarily for
             compatibility but is deprecated and will be removed in a future
@@ -464,9 +481,12 @@ def run_multilayer_theta_search(
             roughness_sigma_nm=roughness_sigma_nm,
             validate_physical_results=validate_physical_results,
             max_reflected_efficiency=max_reflected_efficiency,
-            min_efficiency=min_efficiency,
+            min_reflected_efficiency=min_reflected_efficiency,
             max_total_reflected_efficiency=max_total_reflected_efficiency,
             backend=backend,
+            solver=solver,
+            solver_options=solver_options,
+            polarization=polarization,
         )
         rough_peak_index = int(np.nanargmax(rough_efficiencies))
         rough_peak_angle_deg = float(rough_grazing_angles_deg[rough_peak_index])
@@ -519,9 +539,12 @@ def run_multilayer_theta_search(
             roughness_sigma_nm=roughness_sigma_nm,
             validate_physical_results=validate_physical_results,
             max_reflected_efficiency=max_reflected_efficiency,
-            min_efficiency=min_efficiency,
+            min_reflected_efficiency=min_reflected_efficiency,
             max_total_reflected_efficiency=max_total_reflected_efficiency,
             backend=backend,
+            solver=solver,
+            solver_options=solver_options,
+            polarization=polarization,
         )
         precise_peak_index = int(np.nanargmax(precise_efficiencies))
         precise_ok, precise_status = _peak_capture_status(precise_efficiencies, precise_peak_index, edge_margin=2)
@@ -567,9 +590,12 @@ def run_multilayer_theta_search(
         roughness_sigma_nm=roughness_sigma_nm,
         validate_physical_results=validate_physical_results,
         max_reflected_efficiency=max_reflected_efficiency,
-        min_efficiency=min_efficiency,
+        min_reflected_efficiency=min_reflected_efficiency,
         max_total_reflected_efficiency=max_total_reflected_efficiency,
         backend=backend,
+        solver=solver,
+        solver_options=solver_options,
+        polarization=polarization,
     )
     logger.info(
         "[theta-search][final-scan] done energy=%.6f eV selected_theta=%.6f selected_eff=%.6e",
diff --git a/src/grax/simulation/theta_search_sweep.py b/src/grax/simulation/theta_search_sweep.py
index d925c46..18585c0 100644
--- a/src/grax/simulation/theta_search_sweep.py
+++ b/src/grax/simulation/theta_search_sweep.py
@@ -22,6 +22,7 @@
 from .batch import (
     _case_payload,
     _run_payload,
+    runner_settings as _runner_settings,
     _available_memory_bytes,
     _calibrate_auto_max_workers_from_result,
     _load_checkpoint_case_results,
@@ -222,6 +223,9 @@ def run_multilayer_theta_search_sweep(
     save_profile_plot: bool = True,
     save_stack_plot: bool = True,
     backend: str = "numba",
+    solver: str = "rcwa",
+    solver_options: object | None = None,
+    polarization: str = "s",
 ) -> MultilayerThetaSearchSweepResult:
     """Run a multilayer theta-search sweep and persist standard output artifacts.
 
@@ -275,6 +279,13 @@ def run_multilayer_theta_search_sweep(
             positive energy step in the requested sweep.
         save_profile_plot: Whether to save the grating profile plot.
         save_stack_plot: Whether to save the resolved stack schematic when available.
+        polarization: Incident polarization used for every energy point.
+            ``"s"``/``"TE"`` (default) or ``"p"``/``"TM"``.
+        solver: Electromagnetic solver used for every energy point.
+            ``"rcwa"`` (default) or ``"neviere"``.
+        solver_options: Integration settings for ``solver="neviere"``, as a
+            :class:`grax.NeviereOptions` or an equivalent mapping. Ignored by the
+            selected solver.
         backend: Fourier coefficient backend selector. ``"numba"`` is the
             default backend. ``"numpy"`` remains available temporarily for
             compatibility but is deprecated and will be removed in a future
@@ -409,21 +420,24 @@ def run_multilayer_theta_search_sweep(
         if resumed_case.status == "ok" and diagnostics is not None and diagnostics.precise_fwhm_deg is not None:
             completed_fwhm_by_energy[float(resumed_case.energy_ev)] = float(diagnostics.precise_fwhm_deg)
     progress_bar = (
-        simulation_api.tqdm(total=len(energy_list), desc="RCWA batch", unit="point")
+        simulation_api.tqdm(total=len(energy_list), desc=f"{solver} batch", unit="point")
         if show_progress
         else None
     )
     live_figure: plt.Figure | None = None
     live_axis: plt.Axes | None = None
-    settings = {
-        "default_diffraction_order": diffraction_order,
-        "default_fourier_orders": final_fourier_orders,
-        "max_fourier_orders": max(rough_fourier_orders, fine_fourier_orders, final_fourier_orders),
-        "validate_physical_results": True,
-        "max_reflected_efficiency": 1.05,
-        "min_reflected_efficiency": -1e-8,
-        "backend": backend,
-    }
+    settings = _runner_settings(
+        diffraction_order=diffraction_order,
+        fourier_orders=final_fourier_orders,
+        max_fourier_orders=max(rough_fourier_orders, fine_fourier_orders, final_fourier_orders),
+        validate_physical_results=True,
+        max_reflected_efficiency=1.05,
+        min_reflected_efficiency=-1e-8,
+        backend=backend,
+        solver=solver,
+        solver_options=solver_options,
+        polarization=polarization,
+    )
     retry_jitter_values = _THETA_RETRY_JITTER_DEG[: max(0, int(max_zero_efficiency_retries))]
     theta_continuity_tolerance_deg = 0.02
     def _tracking_metadata_from_case(case: dict[str, object]) -> dict[str, object]:
@@ -1101,6 +1115,9 @@ def _write_single_theta_scan_artifacts(case: CaseExecutionResult, *, skip_if_exi
                 diffraction_angle_all=single.diffraction_angle_all,
                 status="ok",
                 case_data={key: value for key, value in tracked_case.items() if key != "grating"},
+                polarization=single.polarization,
+                solver=single.solver,
+                solver_options=single.solver_options,
                 theta_search_diagnostics=single.theta_search_diagnostics,
                 retry_triggered=single.retry_triggered,
                 retry_attempts=single.retry_attempts,
@@ -1162,7 +1179,10 @@ def _write_single_theta_scan_artifacts(case: CaseExecutionResult, *, skip_if_exi
                     diffraction_angle_all=single.diffraction_angle_all,
                     status="ok",
                     case_data={key: value for key, value in tracked_case.items() if key != "grating"},
-                    theta_search_diagnostics=single.theta_search_diagnostics,
+                    polarization=single.polarization,
+                solver=single.solver,
+                solver_options=single.solver_options,
+                theta_search_diagnostics=single.theta_search_diagnostics,
                     retry_triggered=single.retry_triggered,
                     retry_attempts=single.retry_attempts,
                     retry_status=single.retry_status,
@@ -1296,7 +1316,10 @@ def _latest_available_lower_success(energy_ev: float) -> CaseExecutionResult | N
                         diffraction_angle_all=single.diffraction_angle_all,
                         status="ok",
                         case_data={key: value for key, value in tracked_case.items() if key != "grating"},
-                        theta_search_diagnostics=single.theta_search_diagnostics,
+                        polarization=single.polarization,
+                solver=single.solver,
+                solver_options=single.solver_options,
+                theta_search_diagnostics=single.theta_search_diagnostics,
                         retry_triggered=single.retry_triggered,
                         retry_attempts=single.retry_attempts,
                         retry_status=single.retry_status,
diff --git a/src/grax/slag.py b/src/grax/slag.py
index 0ccda54..24f5f54 100644
--- a/src/grax/slag.py
+++ b/src/grax/slag.py
@@ -8,7 +8,7 @@
 import numpy as np
 
 from .gratings import LaminarGrating
-from .simulation import RCWASimulation
+from .simulation import GratingSimulation
 
 
 @dataclass
@@ -61,7 +61,7 @@ def _build_legacy_grating(config: SlagConfig) -> LaminarGrating:
 def simulate_single_energy(config: SlagConfig, photon_energy_ev: float) -> dict[str, float]:
     """Run the legacy SLAG flow for one energy."""
 
-    simulation = RCWASimulation(
+    simulation = GratingSimulation(
         grating=_build_legacy_grating(config),
         diffraction_order=config.diffraction_order,
         fourier_orders=config.fourier_orders,
@@ -77,7 +77,7 @@ def run_example_slag(
     """Run the legacy SLAG energy sweep helper."""
 
     config = config or default_example_slag_config()
-    simulation = RCWASimulation(
+    simulation = GratingSimulation(
         grating=_build_legacy_grating(config),
         diffraction_order=config.diffraction_order,
         fourier_orders=config.fourier_orders,
diff --git a/src/grax/solvers/__init__.py b/src/grax/solvers/__init__.py
new file mode 100644
index 0000000..404370c
--- /dev/null
+++ b/src/grax/solvers/__init__.py
@@ -0,0 +1,57 @@
+"""Electromagnetic solvers for one-dimensional gratings.
+
+Two independent solvers share the same inputs, the same Fourier-space operators
+(including the Li/Fast-Fourier-Factorization rules for TM), and the same
+efficiency extraction:
+
+- :mod:`grax.solvers.rcwa` - rigorous coupled-wave analysis. Each layer is
+  z-invariant and its field operator is eigen-decomposed once.
+- :mod:`grax.solvers.neviere` - the Nevière differential method. The coupled
+  first-order system is integrated in ``z`` with a fourth-order Runge-Kutta
+  scheme instead of being eigen-decomposed.
+
+Shared machinery lives in :mod:`grax.solvers.common`. Callers normally select a
+solver through ``grax.run_simulation(..., solver=...)`` rather than importing
+these modules directly.
+"""
+
+from __future__ import annotations
+
+from .common import (
+    DiffractionResult,
+    FourierBackend,
+    FourierBackendName,
+    Parameters,
+    Res1Parameters,
+    Res1Result,
+    Res2Parameters,
+    Res2Result,
+    Texture1D,
+    propagating_energy_balance,
+    propagating_order_mask,
+    res0,
+    res1,
+    safe_linalg_solve,
+)
+from .neviere import NeviereOptions, res2_dm
+from .rcwa import res2
+
+__all__ = [
+    "DiffractionResult",
+    "FourierBackend",
+    "FourierBackendName",
+    "NeviereOptions",
+    "Parameters",
+    "Res1Parameters",
+    "Res1Result",
+    "Res2Parameters",
+    "Res2Result",
+    "Texture1D",
+    "propagating_energy_balance",
+    "propagating_order_mask",
+    "res0",
+    "res1",
+    "res2",
+    "res2_dm",
+    "safe_linalg_solve",
+]
diff --git a/src/grax/solvers/common.py b/src/grax/solvers/common.py
new file mode 100644
index 0000000..23a8eed
--- /dev/null
+++ b/src/grax/solvers/common.py
@@ -0,0 +1,1137 @@
+"""Shared data structures and numerics for the 1D grating solvers.
+
+This module holds everything the modal (RCWA) solver in :mod:`grax.solvers.rcwa`
+and the differential-method solver in :mod:`grax.solvers.neviere` have in common:
+the pseudo-periodic Fourier machinery (:func:`res1`), the layer field operators
+including the Li/Fast-Fourier-Factorization rules, the interface-response
+cascade, and the diffraction-efficiency extraction.
+
+The two solvers differ only in how one finite layer is turned into an
+interface-response block: RCWA eigen-decomposes the layer operator, while the
+differential method integrates the equivalent first-order system in ``z``.
+Everything before and after that step is shared, which is what makes the two
+solvers directly comparable.
+"""
+
+from __future__ import annotations
+
+import logging
+from contextlib import nullcontext as _nullcontext
+from dataclasses import dataclass, field
+from enum import Enum
+from time import perf_counter
+from collections.abc import Callable
+from typing import Any, Literal
+
+import numpy as np
+
+from ..roughness import (
+    _apply_debye_waller_roughness as _apply_debye_waller_roughness_impl,
+    _debye_waller_roughness_factor as _debye_waller_roughness_factor_impl,
+    apply_debye_waller_roughness,
+    debye_waller_roughness_diagnostics,
+    incidence_sine_from_beta0,
+)
+from ..simulation._profiling import SolverProfiler
+
+logger = logging.getLogger(__name__)
+
+
+ArrayLike = Any
+EigenCache = dict[tuple[Any, ...], tuple[np.ndarray, np.ndarray]]
+BoundaryBlockCache = dict[tuple[Any, ...], np.ndarray]
+
+# Callable that turns one finite layer into its interface-response block. The
+# modal and differential-method solvers each provide their own implementation.
+LayerBlockFunction = Callable[..., np.ndarray]
+
+# Upper bound on the modal basis size. Beyond this the dense linear algebra
+# becomes impractical and the caller almost certainly wants fewer orders.
+_MAX_BASIS_SIZE = 201
+
+
+class FourierBackend(str, Enum):
+    """Internal Fourier coefficient implementations.
+
+    Two backends are available:
+    - NUMPY: Reference implementation kept for transition-time compatibility
+    - NUMBA: JIT-compiled kernel and the default production path
+    """
+
+    NUMPY = "numpy"
+    NUMBA = "numba"
+
+
+FourierBackendName = Literal["numpy", "numba"]
+
+try:
+    from numba import njit
+
+    _NUMBA_AVAILABLE = True
+except ImportError:  # pragma: no cover - optional dependency
+    njit = None
+    _NUMBA_AVAILABLE = False
+
+
+@dataclass
+class Res1Parameters:
+    trace: int = 0
+
+
+@dataclass
+class Res2Parameters:
+    result: int = 1
+
+
+@dataclass
+class Parameters:
+    dim: int = 1
+    polarization: int = 1
+    not_io: int = 0
+    res1: Res1Parameters = field(default_factory=Res1Parameters)
+    res2: Res2Parameters = field(default_factory=Res2Parameters)
+
+
+@dataclass
+class Texture1D:
+    period: float
+    breaks: np.ndarray
+    refractive_index: np.ndarray
+    epsilon_fourier: np.ndarray
+    homogeneous_index: complex | None = None
+    inv_epsilon_fourier: np.ndarray | None = None
+
+    @property
+    def signature(self) -> tuple[Any, ...]:
+        if self.homogeneous_index is not None:
+            n = self.homogeneous_index
+            return ("homogeneous", round(float(np.real(n)), 12), round(float(np.imag(n)), 12))
+        return (
+            "patterned",
+            tuple(np.round(self.breaks, 12)),
+            tuple((round(float(np.real(v)), 12), round(float(np.imag(v)), 12)) for v in self.refractive_index),
+        )
+
+
+@dataclass
+class Res1Result:
+    wavelength: float
+    period: float
+    orders: np.ndarray
+    beta0: float
+    polarization: int
+    textures: list[Texture1D]
+
+
+@dataclass
+class DiffractionResult:
+    order: np.ndarray
+    theta: np.ndarray
+    efficiency: np.ndarray
+    amplitude: np.ndarray
+
+
+@dataclass
+class Res2Result:
+    inc_top_reflected: DiffractionResult
+    inc_top_transmitted: DiffractionResult
+
+
+if _NUMBA_AVAILABLE:  # pragma: no branch
+    @njit(cache=True)
+    def _piecewise_fourier_coefficients_numba_kernel(
+        breaks: np.ndarray,
+        refractive_index: np.ndarray,
+        period: float,
+        max_order: int,
+    ) -> np.ndarray:
+        """Return Fourier coefficients using a Numba-compiled harmonic loop."""
+
+        harmonic_count = (2 * max_order) + 1
+        coeffs = np.zeros(harmonic_count, dtype=np.complex128)
+        epsilon = refractive_index**2
+        for harmonic_index in range(harmonic_count):
+            order = harmonic_index - max_order
+            if order == 0:
+                total = 0.0 + 0.0j
+                for segment_index in range(epsilon.size):
+                    total += epsilon[segment_index] * (breaks[segment_index + 1] - breaks[segment_index])
+                coeffs[harmonic_index] = total / period
+                continue
+
+            total = 0.0 + 0.0j
+            denominator = -1j * 2.0 * np.pi * order
+            for segment_index in range(epsilon.size):
+                phase_right = np.exp(-1j * 2.0 * np.pi * order * breaks[segment_index + 1] / period)
+                phase_left = np.exp(-1j * 2.0 * np.pi * order * breaks[segment_index] / period)
+                total += epsilon[segment_index] * (phase_right - phase_left) / denominator
+            coeffs[harmonic_index] = total
+        return coeffs
+
+
+def _resolve_fourier_backend(
+    backend: FourierBackendName | str,
+    profiler: SolverProfiler | None = None,
+) -> FourierBackend:
+    """Return the effective Fourier backend after validation."""
+
+    if backend == "numba" and not _NUMBA_AVAILABLE:
+        raise RuntimeError(
+            "numba backend requested but numba is not installed. "
+            "Reinstall the standard graxpy package so the required numba dependency is available."
+        )
+    try:
+        return FourierBackend(backend)
+    except ValueError as error:
+        raise ValueError(f"Unsupported Fourier backend: {backend}") from error
+
+
+def res0(dim: int) -> Parameters:
+    if dim == 0 or abs(dim) != 1:
+        raise NotImplementedError("The Python port currently supports 1D TE/TM-style entry only.")
+    return Parameters(dim=1, polarization=1 if dim > 0 else -1)
+
+
+def res1(
+    wavelength: float,
+    period: float,
+    textures: list[ArrayLike],
+    nn: int | tuple[int, int] | list[int],
+    beta0: float,
+    parm: Parameters | None = None,
+    *,
+    _profiler: SolverProfiler | None = None,
+    _fourier_backend: FourierBackendName | str = "numpy",
+) -> Res1Result:
+    parm = parm or res0(1)
+
+    with _profiler.record("res1_total") if _profiler is not None else _nullcontext():
+        orders = _normalize_orders(nn)
+        harmonic_count = (2 * int(np.max(np.abs(orders)))) + 1
+        resolved_backend = _resolve_fourier_backend(_fourier_backend, _profiler)
+        if _profiler is not None:
+            _profiler.set_metadata("fourier_backend_requested", str(_fourier_backend))
+            _profiler.set_metadata("fourier_backend_actual", resolved_backend.value)
+            _profiler.set_metadata("numba_available", _NUMBA_AVAILABLE)
+            _profiler.set_metadata("texture_count", len(textures))
+            _profiler.set_metadata("input_texture_count", len(textures))
+            _profiler.set_metadata("harmonic_count", harmonic_count)
+        unique_signatures = {_texture_signature_for_metadata(texture, period) for texture in textures}
+        if _profiler is not None:
+            _profiler.set_metadata("unique_texture_signatures", len(unique_signatures))
+        texture_cache: dict[tuple[Any, ...], Texture1D] = {}
+        converted: list[Texture1D] = []
+        cache_hits = 0
+        cache_misses = 0
+        max_order = 2 * int(np.max(np.abs(orders)))
+        for texture in textures:
+            cache_key = (
+                _texture_signature_for_metadata(texture, period),
+                float(period),
+                int(max_order),
+                resolved_backend.value,
+            )
+            if cache_key in texture_cache:
+                converted.append(texture_cache[cache_key])
+                cache_hits += 1
+                if _profiler is not None:
+                    _profiler.add_detail_count("texture_conversion_cache_hits", 1)
+                continue
+            converted_texture = _convert_texture(
+                texture,
+                period,
+                orders,
+                _profiler=_profiler,
+                _fourier_backend=resolved_backend,
+            )
+            texture_cache[cache_key] = converted_texture
+            converted.append(converted_texture)
+            cache_misses += 1
+            if _profiler is not None:
+                _profiler.add_detail_count("texture_conversion_cache_misses", 1)
+        if _profiler is not None:
+            _profiler.set_metadata("texture_conversion_cache_hits", cache_hits)
+            _profiler.set_metadata("texture_conversion_cache_misses", cache_misses)
+    return Res1Result(
+        wavelength=float(wavelength),
+        period=float(period),
+        orders=orders,
+        beta0=float(beta0),
+        polarization=parm.polarization,
+        textures=converted,
+    )
+
+
+def prepare_layer_stack(
+    aa: Res1Result,
+    profile: tuple[ArrayLike, ArrayLike],
+) -> tuple[complex, complex, list[tuple[float, Texture1D]]]:
+    """Validate one profile and return the semi-infinite media and finite layers.
+
+    Args:
+        aa: Fourier-space texture data returned by :func:`res1`.
+        profile: Thickness and texture-index profile for one layer stack.
+
+    Returns:
+        Superstrate index, substrate index, and the compressed finite-layer list
+        where consecutive identical textures have been merged.
+    """
+
+    thicknesses = np.asarray(profile[0], dtype=float)
+    texture_indices = np.asarray(profile[1], dtype=int)
+    if thicknesses.shape != texture_indices.shape:
+        raise ValueError("Profile thicknesses and texture indices must have the same length.")
+    if len(texture_indices) < 2:
+        raise ValueError("The profile must contain at least superstrate and substrate textures.")
+
+    top_texture = aa.textures[int(texture_indices[0])]
+    bottom_texture = aa.textures[int(texture_indices[-1])]
+    if top_texture.homogeneous_index is None or bottom_texture.homogeneous_index is None:
+        raise ValueError("The Python port expects homogeneous superstrate and substrate textures.")
+
+    compressed: list[tuple[float, Texture1D]] = []
+    for thickness, texture_index in zip(thicknesses[1:-1], texture_indices[1:-1]):
+        if thickness <= 0:
+            continue
+        texture = aa.textures[int(texture_index)]
+        if compressed and compressed[-1][1].signature == texture.signature:
+            compressed[-1] = (compressed[-1][0] + float(thickness), texture)
+        else:
+            compressed.append((float(thickness), texture))
+
+    return top_texture.homogeneous_index, bottom_texture.homogeneous_index, compressed
+
+
+def apply_optional_roughness(
+    reflected: DiffractionResult,
+    transmitted: DiffractionResult,
+    *,
+    aa: Res1Result,
+    roughness_sigma_nm: float | None,
+) -> tuple[DiffractionResult, DiffractionResult]:
+    """Apply optional scalar Debye-Waller damping to one solver's output."""
+
+    if roughness_sigma_nm is None:
+        return reflected, transmitted
+
+    diagnostics = debye_waller_roughness_diagnostics(
+        sigma_nm=float(roughness_sigma_nm),
+        wavelength_nm=aa.wavelength,
+        beta0=float(aa.beta0),
+        theta_surface_rad=float(np.arccos(np.clip(float(aa.beta0), -1.0, 1.0))),
+    )
+    logger.debug(
+        "Debye-Waller roughness diagnostics: "
+        "sigma_nm=%(sigma_nm).6g, wavelength_nm=%(wavelength_nm).6g, "
+        "theta_surface_rad=%(theta_surface_rad).6g, "
+        "theta_normal_rad=%(theta_normal_rad).6g, "
+        "beta0=%(beta0).6g, sin_theta_used=%(sin_theta_used).6g, A=%(A).6g, "
+        "A_squared=%(A_squared).6g, damping_factor=%(damping_factor).6g",
+        diagnostics,
+    )
+    return apply_debye_waller_roughness(
+        reflected=reflected,
+        transmitted=transmitted,
+        wavelength_nm=aa.wavelength,
+        beta0=float(aa.beta0),
+        roughness_sigma_nm=float(roughness_sigma_nm),
+    )
+
+
+def _apply_debye_waller_roughness(
+    result: DiffractionResult,
+    *,
+    wavelength_nm: float,
+    incidence_sine: float,
+    roughness_sigma_nm: float,
+) -> DiffractionResult:
+    """Compatibility wrapper for the extracted roughness module."""
+
+    return _apply_debye_waller_roughness_impl(
+        result,
+        wavelength_nm=wavelength_nm,
+        incidence_sine=incidence_sine,
+        roughness_sigma_nm=roughness_sigma_nm,
+    )
+
+
+def _debye_waller_roughness_factor(
+    *,
+    wavelength_nm: float,
+    incidence_sine: float,
+    roughness_sigma_nm: float | None,
+) -> float:
+    """Compatibility wrapper for the extracted roughness module."""
+
+    return _debye_waller_roughness_factor_impl(
+        wavelength_nm=wavelength_nm,
+        incidence_sine=incidence_sine,
+        roughness_sigma_nm=roughness_sigma_nm,
+    )
+
+
+def _incidence_sine_from_beta0(beta0: float) -> float:
+    """Compatibility wrapper for the extracted roughness module."""
+
+    return incidence_sine_from_beta0(beta0)
+
+
+def _normalize_orders(nn: int | tuple[int, int] | list[int]) -> np.ndarray:
+    if np.isscalar(nn):
+        n = int(nn)
+        return np.arange(-n, n + 1, dtype=int)
+    values = np.asarray(nn, dtype=int).ravel()
+    if values.size != 2:
+        raise ValueError("Only scalar or two-value 1D order definitions are supported.")
+    return np.arange(values[0], values[1] + 1, dtype=int)
+
+
+def _convert_texture(
+    texture: ArrayLike,
+    period: float,
+    orders: np.ndarray,
+    *,
+    _profiler: SolverProfiler | None = None,
+    _fourier_backend: FourierBackend = FourierBackend.NUMPY,
+) -> Texture1D:
+    if not isinstance(texture, (list, tuple)):
+        refractive_index = complex(texture)
+        _breaks = np.array([0.0, period], dtype=float)
+        _n = np.array([refractive_index], dtype=complex)
+        _max_order = 2 * int(np.max(np.abs(orders)))
+        return Texture1D(
+            period=period,
+            breaks=_breaks,
+            refractive_index=_n,
+            epsilon_fourier=_piecewise_fourier_coefficients(
+                _breaks, _n, period=period, max_order=_max_order,
+                _profiler=_profiler, _fourier_backend=_fourier_backend,
+            ),
+            homogeneous_index=refractive_index,
+            inv_epsilon_fourier=_piecewise_fourier_coefficients(
+                _breaks, 1.0 / _n, period=period, max_order=_max_order,
+                _profiler=None, _fourier_backend=_fourier_backend,
+            ),
+        )
+
+    if len(texture) == 1:
+        refractive_index = complex(texture[0])
+        return _convert_texture(
+            refractive_index,
+            period,
+            orders,
+            _profiler=_profiler,
+            _fourier_backend=_fourier_backend,
+        )
+
+    if len(texture) != 2:
+        raise ValueError("1D Python textures must be homogeneous or [x_positions, n_left].")
+
+    x_positions = np.asarray(texture[0], dtype=float).ravel()
+    n_left = np.asarray(texture[1], dtype=complex).ravel()
+    if x_positions.size != n_left.size:
+        raise ValueError("Texture boundary and refractive-index vectors must have the same length.")
+    if x_positions.size == 0:
+        raise ValueError("Patterned textures require at least one discontinuity.")
+
+    breaks = np.concatenate(([0.0], x_positions, [period]))
+    refractive_index = np.concatenate((n_left, [n_left[0]]))
+    _max_order = 2 * int(np.max(np.abs(orders)))
+    return Texture1D(
+        period=period,
+        breaks=breaks,
+        refractive_index=refractive_index,
+        epsilon_fourier=_piecewise_fourier_coefficients(
+            breaks, refractive_index, period=period, max_order=_max_order,
+            _profiler=_profiler, _fourier_backend=_fourier_backend,
+        ),
+        inv_epsilon_fourier=_piecewise_fourier_coefficients(
+            breaks, 1.0 / refractive_index, period=period, max_order=_max_order,
+            _profiler=None, _fourier_backend=_fourier_backend,
+        ),
+    )
+
+
+def _texture_signature_for_metadata(texture: ArrayLike, period: float) -> tuple[Any, ...]:
+    """Return a hashable texture signature for one ``res1`` call."""
+
+    if not isinstance(texture, (list, tuple)):
+        value = complex(texture)
+        return ("homogeneous", round(float(np.real(value)), 12), round(float(np.imag(value)), 12))
+
+    if len(texture) == 1:
+        value = complex(texture[0])
+        return ("homogeneous", round(float(np.real(value)), 12), round(float(np.imag(value)), 12))
+
+    x_positions = np.asarray(texture[0], dtype=float).ravel()
+    n_left = np.asarray(texture[1], dtype=complex).ravel()
+    breaks = np.concatenate(([0.0], x_positions, [period]))
+    refractive_index = np.concatenate((n_left, [n_left[0]]))
+    return (
+        "patterned",
+        tuple(np.round(breaks, 12)),
+        tuple(
+            (round(float(np.real(value)), 12), round(float(np.imag(value)), 12))
+            for value in refractive_index
+        ),
+    )
+
+
+def _record_fourier_array_allocations(
+    profiler: SolverProfiler | None,
+    *arrays: np.ndarray,
+) -> None:
+    """Record temporary allocation estimates for Fourier helpers."""
+
+    if profiler is None:
+        return
+    bytes_total = sum(int(array.nbytes) for array in arrays)
+    profiler.add_detail_count("fourier_allocation_bytes", bytes_total)
+    profiler.update_detail_peak("fourier_temp_buffer_bytes_peak", float(bytes_total))
+
+
+def _record_fourier_common_stats(
+    profiler: SolverProfiler | None,
+    refractive_index: np.ndarray,
+    breaks: np.ndarray,
+    max_order: int,
+    backend: FourierBackend,
+) -> None:
+    """Record common Fourier call metadata and counters."""
+
+    if profiler is None:
+        return
+    profiler.add_detail_count("fourier_calls", 1)
+    profiler.add_detail_count("fourier_harmonics_total", (2 * max_order) + 1)
+    profiler.add_detail_count("fourier_segments_total", int(refractive_index.size))
+    profiler.add_detail_count("fourier_backend_calls", 1)
+    profiler.add_unique_value("fourier_backend_actual", backend.value)
+    profiler.update_detail_peak("fourier_segment_count_peak", float(refractive_index.size))
+    profiler.update_detail_peak("fourier_harmonic_count_peak", float((2 * max_order) + 1))
+    _record_fourier_array_allocations(profiler, refractive_index, breaks)
+
+
+def _record_fourier_call_totals(
+    profiler: SolverProfiler | None,
+    total_seconds: float,
+    exp_seconds: float,
+    sum_seconds: float,
+) -> None:
+    """Record comparable detailed Fourier timings across backends."""
+
+    if profiler is None:
+        return
+    overhead_seconds = max(0.0, total_seconds - exp_seconds - sum_seconds)
+    profiler.add_detail_timing("fourier_call_total", total_seconds)
+    profiler.add_detail_timing("fourier_exp", exp_seconds)
+    profiler.add_detail_timing("fourier_sum", sum_seconds)
+    profiler.add_detail_timing("fourier_loop_overhead", overhead_seconds)
+
+
+def _piecewise_fourier_coefficients_baseline(
+    breaks: np.ndarray,
+    refractive_index: np.ndarray,
+    period: float,
+    max_order: int,
+    *,
+    profiler: SolverProfiler | None,
+) -> np.ndarray:
+    """Return Fourier coefficients using the legacy harmonic loop."""
+
+    call_start = perf_counter() if profiler is not None else None
+    g = np.arange(-max_order, max_order + 1, dtype=int)
+    epsilon = refractive_index**2
+    coeffs = np.zeros_like(g, dtype=complex)
+    _record_fourier_array_allocations(profiler, g, epsilon, coeffs)
+
+    exp_seconds = 0.0
+    sum_seconds = 0.0
+    for idx, order in enumerate(g):
+        if profiler is not None:
+            profiler.add_detail_count("fourier_loop_iterations", 1)
+        if order == 0:
+            t0 = perf_counter() if profiler is not None else None
+            coeffs[idx] = np.sum(epsilon * (breaks[1:] - breaks[:-1])) / period
+            if profiler is not None and t0 is not None:
+                sum_seconds += perf_counter() - t0
+                profiler.add_detail_count("fourier_sum_calls", 1)
+            continue
+
+        t0 = perf_counter() if profiler is not None else None
+        phase_right = np.exp(-1j * 2.0 * np.pi * order * breaks[1:] / period)
+        phase_left = np.exp(-1j * 2.0 * np.pi * order * breaks[:-1] / period)
+        if profiler is not None and t0 is not None:
+            exp_seconds += perf_counter() - t0
+            profiler.add_detail_count("fourier_exp_calls", int(phase_right.size + phase_left.size))
+            _record_fourier_array_allocations(profiler, phase_right, phase_left)
+
+        t1 = perf_counter() if profiler is not None else None
+        coeffs[idx] = np.sum(
+            epsilon * (phase_right - phase_left) / (-1j * 2.0 * np.pi * order)
+        )
+        if profiler is not None and t1 is not None:
+            sum_seconds += perf_counter() - t1
+            profiler.add_detail_count("fourier_sum_calls", 1)
+
+    if profiler is not None and call_start is not None:
+        _record_fourier_call_totals(profiler, perf_counter() - call_start, exp_seconds, sum_seconds)
+    return coeffs
+
+
+def _piecewise_fourier_coefficients_numba(
+    breaks: np.ndarray,
+    refractive_index: np.ndarray,
+    period: float,
+    max_order: int,
+    *,
+    profiler: SolverProfiler | None,
+) -> np.ndarray:
+    """Return Fourier coefficients using the Numba kernel."""
+
+    call_start = perf_counter() if profiler is not None else None
+    coeffs = _piecewise_fourier_coefficients_numba_kernel(breaks, refractive_index, period, max_order)
+    if profiler is not None:
+        profiler.add_detail_count("fourier_loop_iterations", int((2 * max_order) + 1))
+        profiler.add_detail_count("fourier_numba_calls", 1)
+        profiler.add_detail_count("fourier_sum_calls", int((2 * max_order) + 1))
+        profiler.add_detail_count("fourier_exp_calls", int((2 * max_order) * 2 * refractive_index.size))
+        _record_fourier_array_allocations(profiler, coeffs)
+    if profiler is not None and call_start is not None:
+        total_seconds = perf_counter() - call_start
+        _record_fourier_call_totals(profiler, total_seconds, total_seconds, 0.0)
+    return coeffs
+
+
+def _piecewise_fourier_coefficients(
+    breaks: np.ndarray,
+    refractive_index: np.ndarray,
+    period: float,
+    max_order: int,
+    *,
+    _profiler: SolverProfiler | None = None,
+    _fourier_backend: FourierBackend = FourierBackend.NUMPY,
+) -> np.ndarray:
+    with _profiler.record("fourier_coefficients") if _profiler is not None else _nullcontext():
+        _record_fourier_common_stats(_profiler, refractive_index, breaks, max_order, _fourier_backend)
+        if _fourier_backend is FourierBackend.NUMPY:
+            return _piecewise_fourier_coefficients_baseline(
+                breaks,
+                refractive_index,
+                period,
+                max_order,
+                profiler=_profiler,
+            )
+        if _fourier_backend is FourierBackend.NUMBA:
+            return _piecewise_fourier_coefficients_numba(
+                breaks,
+                refractive_index,
+                period,
+                max_order,
+                profiler=_profiler,
+            )
+        raise ValueError(f"Unsupported Fourier backend: {_fourier_backend}")
+
+
+def _convolution_matrix(coefficients: np.ndarray, orders: np.ndarray) -> np.ndarray:
+    max_order = (len(coefficients) - 1) // 2
+    coefficient_indices = orders[:, np.newaxis] - orders[np.newaxis, :] + max_order
+    return coefficients[coefficient_indices]
+
+
+@dataclass(frozen=True)
+class LayerFieldOperators:
+    """Fourier-space operators describing one finite layer.
+
+    The tangential field pair ``[F; G]`` (``[E_y; dE_y/dz]`` in TE,
+    ``[H_y; E_x]`` in TM) obeys the first-order system::
+
+        d/dz [F; G] = [[0, A], [B, 0]] [F; G]
+
+    which is equivalent to the second-order form ``d2F/dz2 = (A @ B) F``. The
+    modal solver eigen-decomposes ``operator = A @ B``; the differential method
+    integrates the first-order system directly.
+
+    Attributes:
+        operator: Second-order layer operator ``A @ B``.
+        first_order_a: ``A``. ``None`` means the identity (TE).
+        first_order_b: ``B``.
+        inv_epsilon_conv: TM inverse-permittivity convolution matrix ``[[1/eps]]``
+            used to convert ``dF/dz`` into the tangential electric field.
+            ``None`` in TE.
+    """
+
+    operator: np.ndarray
+    first_order_a: np.ndarray | None
+    first_order_b: np.ndarray
+    inv_epsilon_conv: np.ndarray | None
+
+
+def layer_field_operators(
+    *,
+    texture: Texture1D,
+    orders: np.ndarray,
+    k0: float,
+    kx: np.ndarray,
+    kx_matrix_sq: np.ndarray,
+    polarization: int,
+) -> LayerFieldOperators:
+    """Return the Fourier-space field operators for one finite layer.
+
+    TE uses the direct (Laurent) rule. TM uses the Li/Fast-Fourier-Factorization
+    inverse rule so that the products of the discontinuous permittivity and the
+    discontinuous normal field component converge properly; this is what keeps
+    p-polarized convergence usable for high-contrast profiles.
+
+    Args:
+        texture: Fourier-space texture for the layer.
+        orders: Retained diffraction orders.
+        k0: Vacuum wavenumber.
+        kx: In-plane wavevector for each retained order.
+        kx_matrix_sq: ``diag(kx**2)``, precomputed once per stack.
+        polarization: ``1`` for TE, ``-1`` for TM.
+
+    Returns:
+        Layer operators for both the modal and differential formulations.
+    """
+
+    basis_size = len(orders)
+    epsilon_conv = _convolution_matrix(texture.epsilon_fourier, orders)
+    if polarization == 1:
+        operator = kx_matrix_sq - (k0**2) * epsilon_conv
+        if np.any(np.isnan(operator)) or np.any(np.isinf(operator)):
+            raise ValueError("Layer operator contains NaN/Inf values")
+        return LayerFieldOperators(
+            operator=operator,
+            first_order_a=None,
+            first_order_b=operator,
+            inv_epsilon_conv=None,
+        )
+
+    # TM: Li factorization - A = a1 @ a2
+    # a2 = kx @ inv([eps]) @ kx - k0^2 I
+    # a1 = inv([1/eps])
+    # The correct eigenproblem is a1*a2 (not a2*a1), consistent with
+    # dH/dz = ik0*a1*E_x and dE_x/dz = ik0*a2*H -> d2H/dz2 = -k0^2*a1*a2*H.
+    kx_diag = np.diag(kx)
+    inv_epsilon_conv_tm = _convolution_matrix(texture.inv_epsilon_fourier, orders)
+    inv_eps_matrix = np.linalg.inv(epsilon_conv)
+    inv_inveps_matrix = np.linalg.inv(inv_epsilon_conv_tm)
+    a2 = kx_diag @ inv_eps_matrix @ kx_diag - (k0**2) * np.eye(basis_size)
+    operator = inv_inveps_matrix @ a2
+    if np.any(np.isnan(operator)) or np.any(np.isinf(operator)):
+        raise ValueError("Layer operator contains NaN/Inf values")
+    return LayerFieldOperators(
+        operator=operator,
+        first_order_a=inv_inveps_matrix,
+        first_order_b=a2,
+        inv_epsilon_conv=inv_epsilon_conv_tm,
+    )
+
+
+def solve_stack_from_layer_blocks(
+    *,
+    wavelength: float,
+    period: float,
+    orders: np.ndarray,
+    beta0: float,
+    n_top: complex,
+    n_bottom: complex,
+    polarization: int,
+    layers: list[tuple[float, Texture1D]],
+    layer_block_fn: LayerBlockFunction,
+    _profiler: SolverProfiler | None = None,
+) -> tuple[DiffractionResult, DiffractionResult]:
+    """Solve one 1D stack from per-layer interface-response blocks.
+
+    Each finite layer is represented by its Dirichlet-to-Neumann boundary block.
+    Blocks are cascaded by eliminating shared interface fields, which keeps the
+    propagation stable for deep gratings: no growing exponential is ever formed
+    across the whole stack. ``layer_block_fn`` decides how one layer's block is
+    built, and is the only thing that differs between the modal (RCWA) and
+    differential-method solvers.
+
+    Args:
+        wavelength: Vacuum wavelength in nanometers.
+        period: Grating period in nanometers.
+        orders: Retained diffraction orders.
+        beta0: In-plane incidence direction cosine.
+        n_top: Superstrate refractive index.
+        n_bottom: Substrate refractive index.
+        polarization: ``1`` for TE, ``-1`` for TM.
+        layers: Finite layers as ``(thickness, texture)`` pairs, top to bottom.
+        layer_block_fn: Callable returning one layer's interface-response block.
+        _profiler: Optional solver profiler.
+
+    Returns:
+        Reflected and transmitted diffraction results for incidence from top.
+    """
+
+    k0 = 2 * np.pi / wavelength
+    kx = k0 * beta0 + (2 * np.pi * orders / period)
+    kx_matrix_sq = np.diag(kx**2)
+    basis_size = len(orders)
+
+    kz_top = _kz_branch_array((k0 * n_top) ** 2 - kx**2)
+    kz_bottom = _kz_branch_array((k0 * n_bottom) ** 2 - kx**2)
+    if polarization == 1:
+        derivative_top = 1j * np.diag(kz_top)
+        derivative_bottom = 1j * np.diag(kz_bottom)
+    else:
+        derivative_top = 1j * np.diag(kz_top / n_top**2)
+        derivative_bottom = 1j * np.diag(kz_bottom / n_bottom**2)
+
+    stack_boundary: np.ndarray | None = None
+    with _profiler.record("layer_propagation_cascade") if _profiler is not None else _nullcontext():
+        for thickness, texture in layers:
+            block = layer_block_fn(
+                thickness=thickness,
+                texture=texture,
+                orders=orders,
+                k0=k0,
+                kx=kx,
+                kx_matrix_sq=kx_matrix_sq,
+                polarization=polarization,
+                _profiler=_profiler,
+            )
+            if _profiler is not None:
+                _profiler.add_detail_count("layer_boundary_blocks_constructed", 1)
+                _profiler.update_detail_peak("layer_boundary_block_temp_peak", 1.0)
+                _profiler.update_detail_peak("layer_boundary_block_bytes_peak", float(block.nbytes))
+            if stack_boundary is None:
+                stack_boundary = block
+                continue
+            stack_boundary = _cascade_boundary_pair(
+                stack_boundary,
+                block,
+                basis_size,
+                _profiler=_profiler,
+            )
+    top_stack_admittance = _top_admittance_from_boundary_block(
+        stack_boundary=stack_boundary,
+        derivative_bottom=derivative_bottom,
+    )
+
+    incident = np.zeros(basis_size, dtype=complex)
+    incident[np.where(orders == 0)[0][0]] = 1.0
+
+    with _profiler.record("matrix_solves") if _profiler is not None else _nullcontext():
+        reflected_amplitude = np.linalg.solve(
+            derivative_top + top_stack_admittance,
+            (derivative_top - top_stack_admittance) @ incident,
+        )
+    top_field = incident + reflected_amplitude
+    transmitted_amplitude = _bottom_field_from_boundary_block(
+        top_field=top_field,
+        stack_boundary=stack_boundary,
+        derivative_bottom=derivative_bottom,
+        _profiler=_profiler,
+    )
+
+    incident_kz = kz_top[np.where(orders == 0)[0][0]]
+    if polarization == 1:
+        reflected_efficiency = np.real(kz_top / incident_kz) * np.abs(reflected_amplitude) ** 2
+        transmitted_efficiency = np.real(kz_bottom / incident_kz) * np.abs(transmitted_amplitude) ** 2
+    else:
+        # TM Poynting flux ~ Re(kz/n^2); normalise by incident admittance Re(kz_inc/n_top^2)
+        incident_admittance = np.real(incident_kz / n_top**2)
+        reflected_efficiency = (
+            np.real(kz_top / n_top**2) / incident_admittance * np.abs(reflected_amplitude) ** 2
+        )
+        transmitted_efficiency = (
+            np.real(kz_bottom / n_bottom**2) / incident_admittance * np.abs(transmitted_amplitude) ** 2
+        )
+
+    reflected_theta = _angles_from_kx(kx, k0, n_top)
+    transmitted_theta = _angles_from_kx(kx, k0, n_bottom)
+
+    return (
+        DiffractionResult(
+            order=orders.copy(),
+            theta=reflected_theta,
+            efficiency=reflected_efficiency,
+            amplitude=reflected_amplitude,
+        ),
+        DiffractionResult(
+            order=orders.copy(),
+            theta=transmitted_theta,
+            efficiency=transmitted_efficiency,
+            amplitude=transmitted_amplitude,
+        ),
+    )
+
+
+def propagating_order_mask(
+    *,
+    wavelength: float,
+    period: float,
+    orders: np.ndarray,
+    beta0: float,
+    refractive_index: complex,
+) -> np.ndarray:
+    """Return a mask selecting orders that propagate in one semi-infinite medium.
+
+    Args:
+        wavelength: Vacuum wavelength in nanometers.
+        period: Grating period in nanometers.
+        orders: Retained diffraction orders.
+        beta0: In-plane incidence direction cosine.
+        refractive_index: Refractive index of the medium.
+
+    Returns:
+        Boolean mask that is ``True`` for propagating orders.
+    """
+
+    k0 = 2 * np.pi / wavelength
+    kx = k0 * beta0 + (2 * np.pi * orders / period)
+    kz_squared = (k0 * refractive_index) ** 2 - kx**2
+    return np.real(kz_squared) > 0.0
+
+
+def propagating_energy_balance(
+    reflected: DiffractionResult,
+    transmitted: DiffractionResult,
+    *,
+    wavelength: float,
+    period: float,
+    beta0: float,
+    n_top: complex,
+    n_bottom: complex,
+) -> dict[str, float]:
+    """Return the propagating energy balance for one solve.
+
+    For a lossless structure the total should equal one. For the absorbing
+    materials used in the X-ray regime it is below one, and the shortfall is the
+    absorbed fraction rather than a solver error.
+
+    Args:
+        reflected: Reflected diffraction result.
+        transmitted: Transmitted diffraction result.
+        wavelength: Vacuum wavelength in nanometers.
+        period: Grating period in nanometers.
+        beta0: In-plane incidence direction cosine.
+        n_top: Superstrate refractive index.
+        n_bottom: Substrate refractive index.
+
+    Returns:
+        Reflected, transmitted, and total propagating efficiency sums.
+    """
+
+    reflected_mask = propagating_order_mask(
+        wavelength=wavelength,
+        period=period,
+        orders=np.asarray(reflected.order),
+        beta0=beta0,
+        refractive_index=n_top,
+    )
+    transmitted_mask = propagating_order_mask(
+        wavelength=wavelength,
+        period=period,
+        orders=np.asarray(transmitted.order),
+        beta0=beta0,
+        refractive_index=n_bottom,
+    )
+    reflected_sum = float(np.sum(np.real(np.asarray(reflected.efficiency))[reflected_mask]))
+    transmitted_sum = float(np.sum(np.real(np.asarray(transmitted.efficiency))[transmitted_mask]))
+    return {
+        "reflected": reflected_sum,
+        "transmitted": transmitted_sum,
+        "total": reflected_sum + transmitted_sum,
+    }
+
+
+def _cascade_boundary_pair(
+    left: np.ndarray,
+    right: np.ndarray,
+    basis_size: int,
+    *,
+    _profiler: SolverProfiler | None = None,
+) -> np.ndarray:
+    """Cascade two adjacent interface-response blocks into one block."""
+
+    if _profiler is not None:
+        _profiler.add_detail_count("layer_cascade_pair_calls", 1)
+    with _profiler.record("layer_block_cascade_pair") if _profiler is not None else _nullcontext():
+        with _profiler.record("layer_cascade_pair_partition") if _profiler is not None else _nullcontext():
+            l11 = left[:basis_size, :basis_size]
+            l12 = left[:basis_size, basis_size:]
+            l21 = left[basis_size:, :basis_size]
+            l22 = left[basis_size:, basis_size:]
+            r11 = right[:basis_size, :basis_size]
+            r12 = right[:basis_size, basis_size:]
+            r21 = right[basis_size:, :basis_size]
+            r22 = right[basis_size:, basis_size:]
+
+        with _profiler.record("layer_cascade_pair_matrix_setup") if _profiler is not None else _nullcontext():
+            matrix_to_solve = l22 - r11
+            rhs = np.empty((basis_size, 2 * basis_size), dtype=left.dtype)
+            rhs[:, :basis_size] = l21
+            rhs[:, basis_size:] = r12
+        logger.debug("  _cascade_boundary_pair: solving interface system...")
+        if logger.isEnabledFor(logging.DEBUG):
+            try:
+                cond = np.linalg.cond(matrix_to_solve)
+                if cond > 1e12:
+                    logger.warning(f"  interface matrix is nearly singular (cond={cond:.2e})")
+            except Exception:
+                pass
+
+        try:
+            with _profiler.record("layer_cascade_pair_solve") if _profiler is not None else _nullcontext():
+                solved_blocks = np.linalg.solve(matrix_to_solve, rhs)
+        except np.linalg.LinAlgError as e:
+            logger.error(f"  np.linalg.solve failed in cascade: {e}")
+            raise
+
+        solved_l21 = solved_blocks[:, :basis_size]
+        solved_r12 = solved_blocks[:, basis_size:]
+
+        with _profiler.record("layer_cascade_pair_multiply") if _profiler is not None else _nullcontext():
+            top_left = l11 - (l12 @ solved_l21)
+            top_right = l12 @ solved_r12
+            bottom_left = -(r21 @ solved_l21)
+            bottom_right = r22 + (r21 @ solved_r12)
+
+        with _profiler.record("layer_cascade_pair_assemble") if _profiler is not None else _nullcontext():
+            result = np.empty_like(left)
+            result[:basis_size, :basis_size] = top_left
+            result[:basis_size, basis_size:] = top_right
+            result[basis_size:, :basis_size] = bottom_left
+            result[basis_size:, basis_size:] = bottom_right
+
+            if np.any(np.isnan(result)) or np.any(np.isinf(result)):
+                logger.warning("  cascade produced NaN/Inf values")
+
+    return result
+
+
+def _cascade_layer_boundary_blocks(
+    layer_blocks: list[np.ndarray],
+    basis_size: int,
+    *,
+    _profiler: SolverProfiler | None = None,
+) -> np.ndarray | None:
+    """Return the global interface-response block for all finite layers."""
+
+    if not layer_blocks:
+        return None
+    stack_boundary = layer_blocks[0]
+    with _profiler.record("layer_propagation_cascade") if _profiler is not None else _nullcontext():
+        for block in layer_blocks[1:]:
+            stack_boundary = _cascade_boundary_pair(
+                stack_boundary,
+                block,
+                basis_size,
+                _profiler=_profiler,
+            )
+    return stack_boundary
+
+
+def _top_admittance_from_boundary_block(
+    *,
+    stack_boundary: np.ndarray | None,
+    derivative_bottom: np.ndarray,
+) -> np.ndarray:
+    """Return the top admittance implied by the cascaded layer-response block."""
+
+    if stack_boundary is None:
+        return derivative_bottom
+
+    basis_size = derivative_bottom.shape[0]
+    s11 = stack_boundary[:basis_size, :basis_size]
+    s12 = stack_boundary[:basis_size, basis_size:]
+    s21 = stack_boundary[basis_size:, :basis_size]
+    s22 = stack_boundary[basis_size:, basis_size:]
+    bottom_response = np.linalg.solve(derivative_bottom - s22, s21)
+    return s11 + s12 @ bottom_response
+
+
+def _bottom_field_from_boundary_block(
+    *,
+    top_field: np.ndarray,
+    stack_boundary: np.ndarray | None,
+    derivative_bottom: np.ndarray,
+    _profiler: SolverProfiler | None = None,
+) -> np.ndarray:
+    """Return the substrate field for a boundary-block-cascaded stack."""
+
+    if stack_boundary is None:
+        return top_field
+
+    basis_size = top_field.size
+    s21 = stack_boundary[basis_size:, :basis_size]
+    s22 = stack_boundary[basis_size:, basis_size:]
+    with _profiler.record("matrix_solves") if _profiler is not None else _nullcontext():
+        return np.linalg.solve(derivative_bottom - s22, s21 @ top_field)
+
+
+def _angles_from_kx(kx: np.ndarray, k0: float, refractive_index: complex) -> np.ndarray:
+    if abs(np.imag(refractive_index)) > 1e-12:
+        n_for_angles = np.real(refractive_index)
+    else:
+        n_for_angles = float(np.real(refractive_index))
+    ratio = np.real(kx / (k0 * n_for_angles))
+    ratio = np.clip(ratio, -1.0, 1.0)
+    return np.degrees(np.arcsin(ratio))
+
+
+def _kz_branch(value: complex) -> complex:
+    """Select correct branch for sqrt when computing kz.
+
+    Uses Petit cutoff for branch selection, matching MATLAB's retsqrt(x,0) behavior.
+
+    Args:
+        value: Complex value to compute sqrt of.
+
+    Returns:
+        kz with correct branch selected: imag(kz) > 0, or (imag(kz) == 0 and real(kz) >= 0).
+    """
+    kz = np.sqrt(value + 0j)
+
+    # Petit cutoff: keep if imag > 0, or if (imag == 0 and real >= 0)
+    # Otherwise flip sign
+    if kz.imag < 0 or (np.abs(kz.imag) < 1e-15 and kz.real < 0):
+        kz = -kz
+
+    return kz
+
+
+def _kz_branch_array(values: np.ndarray) -> np.ndarray:
+    """Select the outgoing/decaying sqrt branch for an array of kz values."""
+
+    kz = np.sqrt(np.asarray(values, dtype=complex) + 0j)
+    flip_mask = (np.imag(kz) < 0) | ((np.abs(np.imag(kz)) < 1e-15) & (np.real(kz) < 0))
+    kz[flip_mask] = -kz[flip_mask]
+    return kz
+
+
+def safe_linalg_solve(A: np.ndarray, b: np.ndarray, context: str = "") -> np.ndarray:
+    """Solve linear system with error handling and logging.
+
+    Args:
+        A: Coefficient matrix.
+        b: Right-hand side vector or matrix.
+        context: Context string for logging.
+
+    Returns:
+        Solution vector/matrix.
+
+    Raises:
+        np.linalg.LinAlgError: If the system cannot be solved.
+    """
+    try:
+        cond = np.linalg.cond(A)
+        if cond > 1e10:
+            logger.warning(f"Matrix condition number is high ({cond:.2e}) in {context}")
+        if cond > 1e15:
+            logger.error(f"Matrix is nearly singular ({cond:.2e}) in {context}")
+    except Exception:
+        pass
+
+    try:
+        result = np.linalg.solve(A, b)
+        if np.any(np.isnan(result)) or np.any(np.isinf(result)):
+            logger.error(f"Solution contains NaN/Inf in {context}")
+        return result
+    except np.linalg.LinAlgError as e:
+        logger.error(f"Linear solve failed in {context}: {e}")
+        raise
diff --git a/src/grax/solvers/neviere.py b/src/grax/solvers/neviere.py
new file mode 100644
index 0000000..0ab4213
--- /dev/null
+++ b/src/grax/solvers/neviere.py
@@ -0,0 +1,703 @@
+"""Nevière differential-method solver for 1D gratings.
+
+The differential method expands the fields and the permittivity in the same
+truncated Fourier basis as RCWA, but instead of eigen-decomposing a z-invariant
+layer operator it integrates the resulting coupled first-order system in ``z``
+with a fourth-order Runge-Kutta scheme.
+
+References:
+    Nevière, Vincent & Petit, *Nouv. Rev. Optique* **5**, 65 (1974) - original
+    formulation. Nevière, *J. Opt. Soc. Am. A* **11**, 1835 (1994) - multilayer
+    (Bragg-Fresnel) stacks. Nevière & Popov, *Light Propagation in Periodic
+    Media* (CRC, 2003) - reference treatment including the fast-Fourier-
+    factorization rules for TM.
+
+Formulation
+-----------
+With ``F`` the tangential field (``E_y`` in TE, ``H_y`` in TM) and ``G`` its
+conjugate tangential partner (``dE_y/dz`` in TE, ``E_x = [[1/eps]] dH_y/dz`` in
+TM), Maxwell's equations reduce to::
+
+    d/dz [F; G] = [[0, A], [B, 0]] [F; G]
+
+TE uses ``A = I`` and ``B = Kx^2 - k0^2 [[eps]]``. TM uses the Li /
+fast-Fourier-factorization inverse rule, ``A = [[1/eps]]^-1`` and
+``B = Kx [[eps]]^-1 Kx - k0^2 I``, which is what keeps p-polarized convergence
+usable across a discontinuous permittivity. Both operators are built by
+:func:`grax.solvers.common.layer_field_operators`, shared with the RCWA solver,
+so the two solvers integrate the same truncated system and differ only in how
+they propagate it.
+
+Numerical stability
+-------------------
+A raw transfer matrix is only ever formed across a short sub-block whose optical
+thickness is bounded by ``NeviereOptions.block_phase``, so no growing
+exponential is built up. Each sub-block is converted to a Dirichlet-to-Neumann
+interface-response block and cascaded by
+:func:`grax.solvers.common._cascade_boundary_pair`, which eliminates the shared
+interface fields through a linear solve. That cascade is an R-matrix (impedance)
+propagation, not a transfer-matrix product, so deep gratings and strongly
+evanescent orders stay well conditioned.
+"""
+
+from __future__ import annotations
+
+import logging
+import math
+from contextlib import nullcontext as _nullcontext
+from dataclasses import dataclass
+from collections.abc import Callable
+from typing import Literal
+
+import numpy as np
+
+from ..simulation._profiling import SolverProfiler
+from .common import (
+    ArrayLike,
+    BoundaryBlockCache,
+    FourierBackend,
+    FourierBackendName,
+    Parameters,
+    Res1Result,
+    Res2Result,
+    Texture1D,
+    _MAX_BASIS_SIZE,
+    _cascade_boundary_pair,
+    _convert_texture,
+    _resolve_fourier_backend,
+    apply_optional_roughness,
+    layer_field_operators,
+    prepare_layer_stack,
+    propagating_energy_balance,
+    solve_stack_from_layer_blocks,
+)
+
+logger = logging.getLogger(__name__)
+
+ZSampling = Literal["textures", "continuous"]
+
+
+@dataclass(frozen=True)
+class EpsilonSampler:
+    """Continuous permittivity along ``z`` for one grating at one photon energy.
+
+    Calling the sampler with a depth below the top of the modelled stack returns
+    the Fourier-space permittivity of the grating cut at that depth. Unlike the
+    z-sliced textures, a sampler can be evaluated between solver rows, which is
+    what lets the differential method integrate the true profile.
+
+    Attributes:
+        total_depth_nm: Depth of the modelled stack in nanometers. Taken from the
+            grating geometry rather than from a z-sliced profile, so it does not
+            depend on ``z_resolution_nm``.
+        sample: Maps a depth in nanometers to the permittivity there.
+    """
+
+    total_depth_nm: float
+    sample: Callable[[float], Texture1D]
+
+    def __call__(self, depth_nm: float) -> Texture1D:
+        """Return the Fourier-space permittivity at one depth."""
+
+        return self.sample(depth_nm)
+
+
+@dataclass(frozen=True)
+class NeviereOptions:
+    """Integration settings for the Nevière differential-method solver.
+
+    The step and block sizes are expressed in units of optical phase rather than
+    nanometers so that one setting behaves consistently across photon energies,
+    grazing angles, and Fourier truncation orders. The relevant scale is
+    ``q``, the layer's modal decay/propagation constant; it is bounded per layer
+    from the row norm of the layer operator.
+
+    Attributes:
+        z_sampling: How the permittivity is sampled along ``z``. ``"textures"``
+            integrates through the same z-sliced permittivity the RCWA solver
+            uses, which makes the two solvers directly comparable.
+            ``"continuous"`` re-expands the permittivity from the true grating
+            profile every ``sample_phase`` of optical depth, which is the
+            textbook differential method and does not inherit the staircase
+            approximation. ``"continuous"`` requires a grating and is selected
+            through ``run_simulation``.
+        step_phase: Target ``|q| * h`` for one Runge-Kutta step. Accuracy
+            improves as the fourth power of this value while cost grows far more
+            slowly, because most of the per-layer work is the interface-response
+            conversion and cascade rather than the Runge-Kutta stages: on a
+            lossless dielectric grating, tightening ``0.05 -> 0.02`` improved the
+            energy balance from ``1e-7`` to ``1e-9`` for 30% more runtime.
+        block_phase: Maximum ``|q| * d`` accumulated before a sub-block is
+            converted to an interface-response block and cascaded. Bounds the
+            dynamic range of any transfer matrix that is explicitly formed, and
+            so affects conditioning rather than the converged answer.
+        sample_phase: Optical phase between permittivity samples, used only by
+            ``z_sampling="continuous"``. Unlike ``block_phase`` this one does set
+            accuracy: it is the depth quadrature step at which the true profile
+            is read, so it plays the role ``z_resolution_nm`` plays for the
+            staircase modes. Ignored when ``z_sampling="textures"``.
+        max_step_nm: Optional hard upper bound on the Runge-Kutta step in
+            nanometers, applied on top of ``step_phase``.
+        max_steps_per_layer: Runaway guard on the number of Runge-Kutta steps
+            spent on one layer.
+        energy_balance_tolerance: When set, the summed propagating reflected and
+            transmitted efficiency must not exceed this value or the solve
+            raises. Leave ``None`` to rely on the checks in
+            :func:`grax.run_simulation`. Note that absorbing materials make the
+            balance legitimately smaller than one, so only an upper bound is
+            enforced.
+    """
+
+    z_sampling: ZSampling = "textures"
+    step_phase: float = 0.02
+    block_phase: float = 2.0
+    sample_phase: float = 0.02
+    max_step_nm: float | None = None
+    max_steps_per_layer: int = 4096
+    energy_balance_tolerance: float | None = None
+
+    def __post_init__(self) -> None:
+        """Validate the integration settings."""
+
+        if self.z_sampling not in ("textures", "continuous"):
+            raise ValueError("z_sampling must be 'textures' or 'continuous'.")
+        if not self.step_phase > 0.0:
+            raise ValueError("step_phase must be > 0.")
+        if not self.block_phase > 0.0:
+            raise ValueError("block_phase must be > 0.")
+        if not self.sample_phase > 0.0:
+            raise ValueError("sample_phase must be > 0.")
+        if self.max_step_nm is not None and not self.max_step_nm > 0.0:
+            raise ValueError("max_step_nm must be > 0 when provided.")
+        if self.max_steps_per_layer < 1:
+            raise ValueError("max_steps_per_layer must be >= 1.")
+        if self.energy_balance_tolerance is not None and not self.energy_balance_tolerance > 0.0:
+            raise ValueError("energy_balance_tolerance must be > 0 when provided.")
+
+    def to_dict(self) -> dict[str, object]:
+        """Return a JSON-serializable mapping of the options."""
+
+        return {
+            "z_sampling": self.z_sampling,
+            "step_phase": float(self.step_phase),
+            "block_phase": float(self.block_phase),
+            "sample_phase": float(self.sample_phase),
+            "max_step_nm": None if self.max_step_nm is None else float(self.max_step_nm),
+            "max_steps_per_layer": int(self.max_steps_per_layer),
+            "energy_balance_tolerance": (
+                None
+                if self.energy_balance_tolerance is None
+                else float(self.energy_balance_tolerance)
+            ),
+        }
+
+
+def coerce_neviere_options(options: NeviereOptions | dict[str, object] | None) -> NeviereOptions:
+    """Return a :class:`NeviereOptions` from an options object, mapping, or ``None``.
+
+    Args:
+        options: Options instance, keyword mapping, or ``None`` for defaults.
+
+    Returns:
+        Validated options instance.
+    """
+
+    if options is None:
+        return NeviereOptions()
+    if isinstance(options, NeviereOptions):
+        return options
+    if isinstance(options, dict):
+        return NeviereOptions(**options)  # type: ignore[arg-type]
+    raise TypeError("solver_options must be a NeviereOptions, a mapping, or None.")
+
+
+def res2_dm(
+    aa: Res1Result,
+    profile: tuple[ArrayLike, ArrayLike],
+    parm: Parameters | None = None,
+    *,
+    roughness_sigma_nm: float | None = None,
+    options: NeviereOptions | dict[str, object] | None = None,
+    epsilon_sampler: EpsilonSampler | None = None,
+    _profiler: SolverProfiler | None = None,
+) -> Res2Result:
+    """Solve one layer stack with the Nevière differential method.
+
+    Signature-compatible with :func:`grax.solvers.rcwa.res2` so the two solvers
+    are interchangeable behind ``grax.run_simulation(..., solver=...)``.
+
+    Args:
+        aa: Fourier-space texture data returned by :func:`grax.res1`.
+        profile: Thickness and texture-index profile for one layer stack.
+        parm: Optional solver parameters. Polarization comes from ``aa``.
+        roughness_sigma_nm: Optional rms interface roughness in nanometers,
+            applied as the same scalar Debye-Waller damping the RCWA path uses.
+        options: Integration settings, see :class:`NeviereOptions`.
+        epsilon_sampler: Required when ``options.z_sampling == "continuous"``.
+            Maps a depth below the top of the finite stack, in nanometers, to
+            the Fourier-space permittivity there. Build one with
+            :func:`build_grating_epsilon_sampler`.
+        _profiler: Optional solver profiler.
+
+    Returns:
+        Reflected and transmitted diffraction results for incidence from top.
+    """
+
+    if roughness_sigma_nm is not None and roughness_sigma_nm < 0.0:
+        raise ValueError("roughness_sigma_nm must be >= 0 when provided.")
+
+    resolved_options = coerce_neviere_options(options)
+    if resolved_options.z_sampling == "continuous" and epsilon_sampler is None:
+        raise ValueError(
+            "z_sampling='continuous' requires an epsilon_sampler. Use "
+            "run_simulation(solver='neviere', ...) so the sampler is built from the grating."
+        )
+
+    # Polarization comes from aa (set by res1); parm is ignored for polarization selection.
+    polarization = aa.polarization
+    n_top, n_bottom, layers = prepare_layer_stack(aa, profile)
+
+    if resolved_options.z_sampling == "continuous":
+        layers = _resample_layers_continuously(
+            layers,
+            epsilon_sampler=epsilon_sampler,  # type: ignore[arg-type]
+            options=resolved_options,
+        )
+
+    with _profiler.record("res2_total") if _profiler is not None else _nullcontext():
+        boundary_block_cache: BoundaryBlockCache = {}
+
+        def layer_block_fn(**kwargs: object) -> np.ndarray:
+            return _differential_layer_block(
+                options=resolved_options,
+                boundary_block_cache=boundary_block_cache,
+                **kwargs,  # type: ignore[arg-type]
+            )
+
+        reflected, transmitted = solve_stack_from_layer_blocks(
+            wavelength=aa.wavelength,
+            period=aa.period,
+            orders=aa.orders,
+            beta0=aa.beta0,
+            n_top=n_top,
+            n_bottom=n_bottom,
+            polarization=polarization,
+            layers=layers,
+            layer_block_fn=layer_block_fn,
+            _profiler=_profiler,
+        )
+
+    balance = propagating_energy_balance(
+        reflected,
+        transmitted,
+        wavelength=aa.wavelength,
+        period=aa.period,
+        beta0=aa.beta0,
+        n_top=n_top,
+        n_bottom=n_bottom,
+    )
+    logger.debug(
+        "Neviere energy balance: reflected=%.9g, transmitted=%.9g, total=%.9g",
+        balance["reflected"],
+        balance["transmitted"],
+        balance["total"],
+    )
+    if _profiler is not None:
+        _profiler.set_metadata("neviere_energy_balance_total", balance["total"])
+    tolerance = resolved_options.energy_balance_tolerance
+    if tolerance is not None and balance["total"] > tolerance:
+        raise ValueError(
+            "Nevière differential-method solve violated the energy balance: "
+            f"total propagating efficiency {balance['total']:.9g} exceeds "
+            f"tolerance {tolerance:.9g}. Reduce step_phase or block_phase."
+        )
+
+    reflected, transmitted = apply_optional_roughness(
+        reflected,
+        transmitted,
+        aa=aa,
+        roughness_sigma_nm=roughness_sigma_nm,
+    )
+
+    return Res2Result(
+        inc_top_reflected=reflected,
+        inc_top_transmitted=transmitted,
+    )
+
+
+def _resample_layers_continuously(
+    layers: list[tuple[float, Texture1D]],
+    *,
+    epsilon_sampler: EpsilonSampler,
+    options: NeviereOptions,
+) -> list[tuple[float, Texture1D]]:
+    """Return slabs sampled from the continuous profile instead of the staircase.
+
+    The staircase layers are discarded entirely: both the integration depth and
+    the permittivity come from the grating geometry, so the result does not
+    depend on ``z_resolution_nm``. Each slab carries the permittivity at its
+    midpoint, which makes the depth quadrature second-order accurate. Sub-block
+    splitting and Runge-Kutta stepping then happen inside each slab as usual.
+
+    Args:
+        layers: Compressed staircase layers, used only to bound the slab count
+            and to estimate the permittivity scale.
+        epsilon_sampler: Continuous permittivity for the grating.
+        options: Integration settings.
+
+    Returns:
+        Slabs spanning the stack, carrying continuously sampled permittivities.
+    """
+
+    total_depth_nm = float(epsilon_sampler.total_depth_nm)
+    if total_depth_nm <= 0.0:
+        return layers
+
+    # sample_phase, not block_phase: here the slab thickness sets how finely the
+    # true profile is read along z, which is an accuracy knob, not a
+    # conditioning one.
+    scale = max(
+        (_spectral_scale_from_texture(texture) for _, texture in layers),
+        default=1.0,
+    )
+    target_nm = options.sample_phase / scale if scale > 0.0 else total_depth_nm
+    if options.max_step_nm is not None:
+        target_nm = min(target_nm, options.max_step_nm)
+    slab_count = max(1, int(math.ceil(total_depth_nm / max(target_nm, 1e-12))))
+    slab_count = min(slab_count, options.max_steps_per_layer * max(len(layers), 1))
+    slab_nm = total_depth_nm / slab_count
+
+    return [
+        (slab_nm, epsilon_sampler((index + 0.5) * slab_nm))
+        for index in range(slab_count)
+    ]
+
+
+def build_grating_epsilon_sampler(
+    grating: object,
+    *,
+    photon_energy_ev: float,
+    period_nm: float,
+    orders: np.ndarray,
+    n_inc: complex = 1.0 + 0.0j,
+    fourier_backend: FourierBackendName | str = "numba",
+) -> EpsilonSampler:
+    """Return a continuous permittivity sampler for one grating.
+
+    The sampler evaluates the grating's material stack at an arbitrary depth
+    rather than on the discrete solver z-grid, and Fourier-expands that cut. It
+    is what makes ``z_sampling="continuous"`` integrate the true profile instead
+    of a staircase approximation of it.
+
+    Args:
+        grating: Grating derived from :class:`grax.BaseGrating`.
+        photon_energy_ev: Photon energy used to resolve optical constants.
+        period_nm: Grating period spanned by the sampler in nanometers.
+        orders: Retained diffraction orders.
+        n_inc: Incident-medium refractive index.
+        fourier_backend: Fourier coefficient backend selector.
+
+    Returns:
+        Sampler mapping a depth below the top of the modelled stack, in
+        nanometers, to a Fourier-space texture.
+    """
+
+    from ..materials import resolve_refractive_index
+
+    resolved_backend: FourierBackend = _resolve_fourier_backend(fourier_backend)
+    coating_stack = grating.resolved_stack()  # type: ignore[attr-defined]
+    n_sub = complex(resolve_refractive_index(coating_stack.substrate_material, photon_energy_ev))
+    num_periods = grating._roughness_num_supercells()  # type: ignore[attr-defined]
+    x_grid = grating._build_x_grid(num_periods=num_periods)  # type: ignore[attr-defined]
+    z_grid = grating._build_solver_z_grid(coating_stack)  # type: ignore[attr-defined]
+    surface = grating._surface_profile_on_grid(x_grid, num_periods=num_periods)  # type: ignore[attr-defined]
+    z_top_nm = float(z_grid[0])
+
+    cache: dict[float, Texture1D] = {}
+
+    def sampler(depth_nm: float) -> Texture1D:
+        key = round(float(depth_nm), 9)
+        cached = cache.get(key)
+        if cached is not None:
+            return cached
+        descriptor = grating._texture_descriptor_for_row(  # type: ignore[attr-defined]
+            z_value=z_top_nm - float(depth_nm),
+            x_grid=x_grid,
+            surface=surface,
+            coating_stack=coating_stack,
+            photon_energy_ev=photon_energy_ev,
+            n_inc=complex(n_inc),
+            n_sub=n_sub,
+        )
+        texture = _convert_texture(
+            descriptor,
+            period_nm,
+            orders,
+            _fourier_backend=resolved_backend,
+        )
+        cache[key] = texture
+        return texture
+
+    # The solver z grid runs from the top of the modelled stack down to zero, so
+    # its first entry is the stack depth. Reading it here rather than summing a
+    # z-sliced profile keeps the continuous mode independent of z_resolution_nm.
+    return EpsilonSampler(total_depth_nm=z_top_nm, sample=sampler)
+
+
+def _spectral_scale_from_texture(texture: Texture1D) -> float:
+    """Return a crude propagation-constant scale from a texture alone.
+
+    Used only to pick a slab thickness before any layer operator exists.
+    """
+
+    magnitude = float(np.max(np.abs(texture.epsilon_fourier)))
+    return max(math.sqrt(magnitude), 1e-12)
+
+
+def _spectral_scale(operator: np.ndarray) -> float:
+    """Return an upper bound on ``|q|`` for one layer operator.
+
+    ``operator`` has eigenvalues ``q**2``. The induced infinity norm (the largest
+    absolute row sum) bounds the spectral radius, and is tight for the nearly
+    diagonal operators produced by the low-contrast permittivities typical of
+    X-ray optics.
+
+    Args:
+        operator: Second-order layer operator.
+
+    Returns:
+        Bound on the magnitude of the layer's propagation constants.
+    """
+
+    row_sums = np.sum(np.abs(operator), axis=1)
+    largest = float(np.max(row_sums)) if row_sums.size else 0.0
+    return math.sqrt(max(largest, 0.0))
+
+
+def _rk4_constant_propagator(system: np.ndarray, step_nm: float) -> np.ndarray:
+    """Return the RK4 propagator for a z-invariant first-order system.
+
+    For a constant coefficient matrix ``M`` the classical fourth-order
+    Runge-Kutta update reduces exactly to the fourth-order truncation of
+    ``exp(M h)``.
+
+    Args:
+        system: Coefficient matrix ``M``.
+        step_nm: Step size ``h`` in nanometers.
+
+    Returns:
+        Propagator advancing the state by one step.
+    """
+
+    scaled = system * step_nm
+    size = scaled.shape[0]
+    propagator = np.eye(size, dtype=complex)
+    term = np.eye(size, dtype=complex)
+    for order in range(1, 5):
+        term = (term @ scaled) / order
+        propagator = propagator + term
+    return propagator
+
+
+def _rk4_fundamental_matrix(
+    system: np.ndarray,
+    thickness_nm: float,
+    step_count: int,
+) -> np.ndarray:
+    """Return the fundamental solution across one z-invariant slab.
+
+    Args:
+        system: Coefficient matrix of the first-order system.
+        thickness_nm: Slab thickness in nanometers.
+        step_count: Number of Runge-Kutta steps across the slab.
+
+    Returns:
+        Transfer matrix mapping the state at the top of the slab to the bottom.
+    """
+
+    step_nm = thickness_nm / step_count
+    propagator = _rk4_constant_propagator(system, step_nm)
+    result = propagator
+    for _ in range(step_count - 1):
+        result = result @ propagator
+    return result
+
+
+def _first_order_system(
+    first_order_a: np.ndarray | None,
+    first_order_b: np.ndarray,
+) -> np.ndarray:
+    """Assemble ``[[0, A], [B, 0]]`` for the coupled first-order system."""
+
+    basis_size = first_order_b.shape[0]
+    system = np.zeros((2 * basis_size, 2 * basis_size), dtype=complex)
+    if first_order_a is None:
+        system[:basis_size, basis_size:] = np.eye(basis_size, dtype=complex)
+    else:
+        system[:basis_size, basis_size:] = first_order_a
+    system[basis_size:, :basis_size] = first_order_b
+    return system
+
+
+def _boundary_block_from_transfer(transfer: np.ndarray, basis_size: int) -> np.ndarray:
+    """Convert a slab transfer matrix into an interface-response block.
+
+    ``transfer`` maps ``[F; G]`` at the top of the slab to ``[F; G]`` at the
+    bottom. The cascade routine instead needs the Dirichlet-to-Neumann block
+    mapping ``[F_top; F_bottom]`` to ``[G_top; G_bottom]``, which for a
+    homogeneous slab reproduces the modal ``[[-q coth(qd), q csch(qd)],
+    [-q csch(qd), q coth(qd)]]`` exactly.
+
+    Args:
+        transfer: Slab transfer matrix.
+        basis_size: Number of retained orders.
+
+    Returns:
+        Interface-response block for the slab.
+    """
+
+    t11 = transfer[:basis_size, :basis_size]
+    t12 = transfer[:basis_size, basis_size:]
+    t21 = transfer[basis_size:, :basis_size]
+    t22 = transfer[basis_size:, basis_size:]
+
+    rhs = np.empty((basis_size, 2 * basis_size), dtype=complex)
+    rhs[:, :basis_size] = t11
+    rhs[:, basis_size:] = np.eye(basis_size, dtype=complex)
+    try:
+        solved = np.linalg.solve(t12, rhs)
+    except np.linalg.LinAlgError as error:
+        raise ValueError(
+            "Nevière slab transfer matrix is singular. Reduce block_phase so "
+            "shorter sub-blocks are cascaded."
+        ) from error
+    t12_inv_t11 = solved[:, :basis_size]
+    t12_inv = solved[:, basis_size:]
+
+    block = np.empty((2 * basis_size, 2 * basis_size), dtype=complex)
+    block[:basis_size, :basis_size] = -t12_inv_t11
+    block[:basis_size, basis_size:] = t12_inv
+    block[basis_size:, :basis_size] = t21 - (t22 @ t12_inv_t11)
+    block[basis_size:, basis_size:] = t22 @ t12_inv
+    if np.any(np.isnan(block)) or np.any(np.isinf(block)):
+        raise ValueError("Nevière layer block produced NaN/Inf values")
+    return block
+
+
+def _differential_layer_block(
+    *,
+    thickness: float,
+    texture: Texture1D,
+    orders: np.ndarray,
+    k0: float,
+    kx: np.ndarray,
+    kx_matrix_sq: np.ndarray,
+    polarization: int,
+    options: NeviereOptions,
+    boundary_block_cache: BoundaryBlockCache,
+    _profiler: SolverProfiler | None = None,
+) -> np.ndarray:
+    """Return the interface-response block for one layer by RK4 integration."""
+
+    basis_size = len(orders)
+    if basis_size > _MAX_BASIS_SIZE:
+        raise ValueError(
+            f"Fourier orders too large: {basis_size} modes. "
+            "Try reducing fourier_orders to 50 or less."
+        )
+
+    cache_key = (
+        texture.signature,
+        float(thickness),
+        tuple(int(order) for order in orders),
+        float(k0),
+        int(polarization),
+    )
+    cached_block = boundary_block_cache.get(cache_key)
+    if cached_block is not None:
+        if _profiler is not None:
+            _profiler.add_detail_count("layer_boundary_block_cache_hits", 1)
+        return cached_block
+    if _profiler is not None:
+        _profiler.add_detail_count("layer_boundary_block_cache_misses", 1)
+
+    with _profiler.record("layer_operator_build") if _profiler is not None else _nullcontext():
+        operators = layer_field_operators(
+            texture=texture,
+            orders=orders,
+            k0=k0,
+            kx=kx,
+            kx_matrix_sq=kx_matrix_sq,
+            polarization=polarization,
+        )
+        system = _first_order_system(operators.first_order_a, operators.first_order_b)
+
+    scale = _spectral_scale(operators.operator)
+    block_count, step_count = _resolve_integration_schedule(
+        thickness_nm=float(thickness),
+        scale=scale,
+        options=options,
+    )
+    if _profiler is not None:
+        _profiler.add_detail_count("neviere_sub_blocks", block_count)
+        _profiler.add_detail_count("neviere_rk4_steps", block_count * step_count)
+        total_steps = float(block_count * step_count)
+        _profiler.update_detail_peak("neviere_steps_per_layer_peak", total_steps)
+
+    sub_thickness_nm = float(thickness) / block_count
+    integration_stage = (
+        _profiler.record("neviere_layer_integration") if _profiler is not None else _nullcontext()
+    )
+    with integration_stage:
+        transfer = _rk4_fundamental_matrix(system, sub_thickness_nm, step_count)
+        sub_block = _boundary_block_from_transfer(transfer, basis_size)
+
+    block = sub_block
+    if block_count > 1:
+        cascade_stage = (
+            _profiler.record("layer_propagation_cascade")
+            if _profiler is not None
+            else _nullcontext()
+        )
+        with cascade_stage:
+            for _ in range(block_count - 1):
+                block = _cascade_boundary_pair(
+                    block,
+                    sub_block,
+                    basis_size,
+                    _profiler=_profiler,
+                )
+
+    boundary_block_cache[cache_key] = block
+    return block
+
+
+def _resolve_integration_schedule(
+    *,
+    thickness_nm: float,
+    scale: float,
+    options: NeviereOptions,
+) -> tuple[int, int]:
+    """Return the sub-block count and per-block Runge-Kutta step count.
+
+    Both are derived from the layer's optical thickness ``scale * thickness_nm``:
+    ``block_phase`` bounds how much phase one explicitly formed transfer matrix
+    may span, and ``step_phase`` bounds the phase per Runge-Kutta step.
+
+    Args:
+        thickness_nm: Layer thickness in nanometers.
+        scale: Bound on the layer's propagation constants.
+        options: Integration settings.
+
+    Returns:
+        Number of cascaded sub-blocks and Runge-Kutta steps per sub-block.
+    """
+
+    optical_thickness = scale * max(thickness_nm, 0.0)
+    block_count = max(1, int(math.ceil(optical_thickness / options.block_phase)))
+    sub_thickness_nm = thickness_nm / block_count
+    step_count = max(1, int(math.ceil((optical_thickness / block_count) / options.step_phase)))
+    if options.max_step_nm is not None:
+        step_count = max(step_count, int(math.ceil(sub_thickness_nm / options.max_step_nm)))
+    step_count = min(step_count, options.max_steps_per_layer)
+    return block_count, step_count
diff --git a/src/grax/solvers/rcwa.py b/src/grax/solvers/rcwa.py
new file mode 100644
index 0000000..62d49cb
--- /dev/null
+++ b/src/grax/solvers/rcwa.py
@@ -0,0 +1,356 @@
+"""Rigorous coupled-wave (modal) solver for 1D gratings.
+
+Each finite layer is treated as z-invariant, its Fourier-space field operator is
+eigen-decomposed once, and the resulting modal admittances are assembled into a
+Dirichlet-to-Neumann interface-response block. Blocks are cascaded by the shared
+routine in :mod:`grax.solvers.common`, which also extracts the diffraction
+efficiencies.
+
+The differential-method solver in :mod:`grax.solvers.neviere` replaces only the
+per-layer block construction; everything else is shared, so the two solvers can
+be compared directly.
+"""
+
+from __future__ import annotations
+
+import hashlib
+import logging
+from contextlib import nullcontext as _nullcontext
+from time import perf_counter
+
+import numpy as np
+
+from ..simulation._profiling import SolverProfiler
+from .common import (
+    ArrayLike,
+    BoundaryBlockCache,
+    EigenCache,
+    Parameters,
+    Res1Result,
+    Res2Result,
+    Texture1D,
+    _MAX_BASIS_SIZE,
+    apply_optional_roughness,
+    layer_field_operators,
+    prepare_layer_stack,
+    solve_stack_from_layer_blocks,
+)
+
+logger = logging.getLogger(__name__)
+
+
+def res2(
+    aa: Res1Result,
+    profile: tuple[ArrayLike, ArrayLike],
+    parm: Parameters | None = None,
+    *,
+    roughness_sigma_nm: float | None = None,
+    _profiler: SolverProfiler | None = None,
+) -> Res2Result:
+    """Solve the RCWA layer stack.
+
+    Args:
+        aa: Fourier-space texture data returned by :func:`grax.res1`.
+        profile: Thickness and texture-index profile for one RCWA layer stack.
+        parm: Optional solver parameters.
+        roughness_sigma_nm: Optional rms interface roughness in nanometers. When
+            provided, reflected and transmitted diffraction efficiencies are
+            uniformly damped by a scalar Debye-Waller factor,
+            ``exp(-(4*pi*sigma*sin(theta)/wavelength)^2)``. Here ``theta`` is
+            the grazing incidence angle from the surface. This simple model
+            reduces total intensity to mimic scattering losses; it does not
+            alter geometry, RCWA matrices, diffraction amplitudes, or introduce
+            stochastic rough surfaces.
+
+    Returns:
+        Reflected and transmitted diffraction results for incidence from top.
+    """
+
+    if roughness_sigma_nm is not None and roughness_sigma_nm < 0.0:
+        raise ValueError("roughness_sigma_nm must be >= 0 when provided.")
+
+    # Polarization comes from aa (set by res1); parm is ignored for polarization selection.
+    polarization = aa.polarization
+    n_top, n_bottom, layers = prepare_layer_stack(aa, profile)
+
+    with _profiler.record("res2_total") if _profiler is not None else _nullcontext():
+        reflected, transmitted = _solve_modal_stack(
+            wavelength=aa.wavelength,
+            period=aa.period,
+            orders=aa.orders,
+            beta0=aa.beta0,
+            n_top=n_top,
+            n_bottom=n_bottom,
+            polarization=polarization,
+            layers=layers,
+            _profiler=_profiler,
+        )
+
+    reflected, transmitted = apply_optional_roughness(
+        reflected,
+        transmitted,
+        aa=aa,
+        roughness_sigma_nm=roughness_sigma_nm,
+    )
+
+    return Res2Result(
+        inc_top_reflected=reflected,
+        inc_top_transmitted=transmitted,
+    )
+
+
+def _solve_te_stack(
+    wavelength: float,
+    period: float,
+    orders: np.ndarray,
+    beta0: float,
+    n_top: complex,
+    n_bottom: complex,
+    layers: list[tuple[float, Texture1D]],
+    *,
+    _profiler: SolverProfiler | None = None,
+):
+    """Solve the 1D TE stack with modal layer blocks."""
+
+    return _solve_modal_stack(
+        wavelength=wavelength,
+        period=period,
+        orders=orders,
+        beta0=beta0,
+        n_top=n_top,
+        n_bottom=n_bottom,
+        polarization=1,
+        layers=layers,
+        _profiler=_profiler,
+    )
+
+
+def _solve_tm_stack(
+    wavelength: float,
+    period: float,
+    orders: np.ndarray,
+    beta0: float,
+    n_top: complex,
+    n_bottom: complex,
+    layers: list[tuple[float, Texture1D]],
+    *,
+    _profiler: SolverProfiler | None = None,
+):
+    """Solve the 1D TM stack with modal layer blocks.
+
+    Uses the inverse-permittivity convolution operator and TM boundary
+    admittances. Only the layer operator and the semi-infinite derivatives
+    differ from the TE path.
+    """
+
+    return _solve_modal_stack(
+        wavelength=wavelength,
+        period=period,
+        orders=orders,
+        beta0=beta0,
+        n_top=n_top,
+        n_bottom=n_bottom,
+        polarization=-1,
+        layers=layers,
+        _profiler=_profiler,
+    )
+
+
+def _solve_modal_stack(
+    *,
+    wavelength: float,
+    period: float,
+    orders: np.ndarray,
+    beta0: float,
+    n_top: complex,
+    n_bottom: complex,
+    polarization: int,
+    layers: list[tuple[float, Texture1D]],
+    _profiler: SolverProfiler | None = None,
+):
+    """Solve one 1D stack using eigen-decomposed modal layer blocks."""
+
+    eigen_cache: EigenCache = {}
+    boundary_block_cache: BoundaryBlockCache = {}
+
+    def layer_block_fn(**kwargs: object) -> np.ndarray:
+        return _layer_boundary_block(
+            eigen_cache=eigen_cache,
+            boundary_block_cache=boundary_block_cache,
+            **kwargs,  # type: ignore[arg-type]
+        )
+
+    return solve_stack_from_layer_blocks(
+        wavelength=wavelength,
+        period=period,
+        orders=orders,
+        beta0=beta0,
+        n_top=n_top,
+        n_bottom=n_bottom,
+        polarization=polarization,
+        layers=layers,
+        layer_block_fn=layer_block_fn,
+        _profiler=_profiler,
+    )
+
+
+def _layer_boundary_block(
+    *,
+    thickness: float,
+    texture: Texture1D,
+    orders: np.ndarray,
+    k0: float,
+    kx: np.ndarray,
+    kx_matrix_sq: np.ndarray,
+    polarization: int = 1,
+    eigen_cache: EigenCache,
+    boundary_block_cache: BoundaryBlockCache,
+    _profiler: SolverProfiler | None = None,
+) -> np.ndarray:
+    """Return the interface-response block for one finite RCWA layer."""
+
+    basis_size = len(orders)
+    logger.debug(f"  _layer_boundary_block: thickness={thickness:.4f} nm, basis_size={basis_size}")
+
+    if basis_size > _MAX_BASIS_SIZE:
+        raise ValueError(f"Fourier orders too large: {basis_size} modes. "
+                        "Try reducing fourier_orders to 50 or less.")
+
+    boundary_cache_key = (
+        texture.signature,
+        float(thickness),
+        tuple(int(order) for order in orders),
+        float(k0),
+        int(polarization),
+    )
+    cached_block = boundary_block_cache.get(boundary_cache_key)
+    if cached_block is not None:
+        if _profiler is not None:
+            _profiler.add_detail_count("layer_boundary_block_cache_hits", 1)
+        return cached_block
+    if _profiler is not None:
+        _profiler.add_detail_count("layer_boundary_block_cache_misses", 1)
+
+    with _profiler.record("layer_operator_build") if _profiler is not None else _nullcontext():
+        operators = layer_field_operators(
+            texture=texture,
+            orders=orders,
+            k0=k0,
+            kx=kx,
+            kx_matrix_sq=kx_matrix_sq,
+            polarization=polarization,
+        )
+        operator = operators.operator
+        inv_epsilon_conv_tm = operators.inv_epsilon_conv
+
+    cache_key = (
+        texture.signature,
+        tuple(int(order) for order in orders),
+        float(k0),
+        int(polarization),
+    )
+    if _profiler is not None:
+        operator_key = hashlib.sha1(operator.tobytes()).hexdigest()
+        _profiler.add_unique_value("layer_operator_unique", operator_key)
+        _profiler.add_detail_count("layer_operator_rows_total", int(operator.shape[0]))
+        _profiler.add_detail_count("layer_operator_cols_total", int(operator.shape[1]))
+        _profiler.add_detail_count("layer_operator_calls", 1)
+        _profiler.update_detail_peak("layer_operator_rows_peak", float(operator.shape[0]))
+        _profiler.update_detail_peak("layer_operator_cols_peak", float(operator.shape[1]))
+    if cache_key in eigen_cache:
+        eigenvalues, eigenvectors = eigen_cache[cache_key]
+        if _profiler is not None:
+            _profiler.add_detail_count("layer_eigensolve_cache_hits", 1)
+    else:
+        if _profiler is not None:
+            _profiler.add_detail_count("layer_eigensolve_cache_misses", 1)
+        with _profiler.record("layer_eigensolve") if _profiler is not None else _nullcontext():
+            t0 = perf_counter() if _profiler is not None else None
+            eigenvalues, eigenvectors = np.linalg.eig(operator)
+            if _profiler is not None and t0 is not None:
+                _profiler.add_detail_timing("layer_eigensolve_call", perf_counter() - t0)
+        eigen_cache[cache_key] = (eigenvalues, eigenvectors)
+    if _profiler is not None:
+        _profiler.increment("layer_eigensolve_calls")
+
+    with _profiler.record("layer_modal_values") if _profiler is not None else _nullcontext():
+        q_values = np.sqrt(eigenvalues + 0j)
+        q_coth = _modal_q_coth(q_values, thickness)
+        q_csch = _modal_q_csch(q_values, thickness)
+    with _profiler.record("layer_modal_matrices") if _profiler is not None else _nullcontext():
+        t0 = perf_counter() if _profiler is not None else None
+        admittance, coupling = _modal_function_matrices(eigenvectors, q_coth, q_csch)
+        if _profiler is not None and t0 is not None:
+            _profiler.add_detail_timing("layer_modal_matrices_call", perf_counter() - t0)
+            _profiler.add_detail_count("layer_modal_matrices_calls", 1)
+    with _profiler.record("layer_block_assembly") if _profiler is not None else _nullcontext():
+        if polarization == -1 and inv_epsilon_conv_tm is not None:
+            # TM: block tracks [H; E_x] where E_x = [1/eps] @ dH/dz
+            admittance = inv_epsilon_conv_tm @ admittance
+            coupling = inv_epsilon_conv_tm @ coupling
+        block = np.empty((2 * basis_size, 2 * basis_size), dtype=complex)
+        block[:basis_size, :basis_size] = -admittance
+        block[:basis_size, basis_size:] = coupling
+        block[basis_size:, :basis_size] = -coupling
+        block[basis_size:, basis_size:] = admittance
+    boundary_block_cache[boundary_cache_key] = block
+    return block
+
+
+def _modal_q_coth(q_values: np.ndarray, thickness: float) -> np.ndarray:
+    """Return modal ``q / tanh(q * thickness)`` with a small-argument limit."""
+
+    argument = q_values * thickness
+    values = np.empty_like(q_values, dtype=complex)
+    small = np.abs(argument) < 1e-8
+    values[small] = (1.0 / thickness) + (q_values[small] ** 2 * thickness / 3.0)
+    values[~small] = q_values[~small] / np.tanh(argument[~small])
+    return values
+
+
+def _modal_q_csch(q_values: np.ndarray, thickness: float) -> np.ndarray:
+    """Return modal ``q / sinh(q * thickness)`` with a small-argument limit."""
+
+    argument = q_values * thickness
+    values = np.empty_like(q_values, dtype=complex)
+    small = np.abs(argument) < 1e-8
+    values[small] = (1.0 / thickness) - (q_values[small] ** 2 * thickness / 6.0)
+    values[~small] = q_values[~small] / np.sinh(argument[~small])
+    return values
+
+
+def _modal_function_matrix(
+    eigenvectors: np.ndarray,
+    modal_values: np.ndarray,
+) -> np.ndarray:
+    """Return ``V @ diag(modal_values) @ V^-1`` without forming ``V^-1``."""
+
+    left_factor = eigenvectors * modal_values[np.newaxis, :]
+    result = np.linalg.solve(eigenvectors.T, left_factor.T).T
+    if np.any(np.isnan(result)) or np.any(np.isinf(result)):
+        raise ValueError("Modal layer function produced NaN/Inf values")
+    return result
+
+
+def _modal_function_matrices(
+    eigenvectors: np.ndarray,
+    first_modal_values: np.ndarray,
+    second_modal_values: np.ndarray,
+) -> tuple[np.ndarray, np.ndarray]:
+    """Return two ``V @ diag(m) @ V^-1`` matrices from one shared solve."""
+
+    first_left_factor = eigenvectors * first_modal_values[np.newaxis, :]
+    second_left_factor = eigenvectors * second_modal_values[np.newaxis, :]
+    stacked_rhs = np.hstack((first_left_factor.T, second_left_factor.T))
+    solved = np.linalg.solve(eigenvectors.T, stacked_rhs)
+    split_index = eigenvectors.shape[0]
+    first_result = solved[:, :split_index].T
+    second_result = solved[:, split_index:].T
+    if (
+        np.any(np.isnan(first_result))
+        or np.any(np.isinf(first_result))
+        or np.any(np.isnan(second_result))
+        or np.any(np.isinf(second_result))
+    ):
+        raise ValueError("Modal layer function produced NaN/Inf values")
+    return first_result, second_result
diff --git a/src/grax/stacks.py b/src/grax/stacks.py
index d0d25fe..66edd59 100644
--- a/src/grax/stacks.py
+++ b/src/grax/stacks.py
@@ -12,6 +12,16 @@
 from .materials import material_label
 
 
+@dataclass(frozen=True)
+class _SchematicRepeatUnit:
+    """Metadata for one representative repeated bilayer in a schematic."""
+
+    layer_start_index_top_down: int
+    bilayer_count: int
+    bilayer_period_nm: float
+    materials_bottom_up: tuple[Any, Any]
+
+
 @dataclass
 class BaseStack(ABC):
     """Base class for coating stacks applied on top of a grating substrate."""
@@ -110,7 +120,7 @@ def _schematic_layers_and_summary(
         self,
         *,
         max_layers: int | None = None,
-    ) -> tuple[list[tuple[Any, float]], list[str]]:
+    ) -> tuple[list[tuple[Any, float]], list[str], _SchematicRepeatUnit | None]:
         """Return schematic layers and summary lines for stack plotting.
 
         Args:
@@ -118,7 +128,8 @@ def _schematic_layers_and_summary(
                 stack rendering.
 
         Returns:
-            A tuple containing top-down schematic layers and summary lines.
+            A tuple containing top-down schematic layers, summary lines, and
+            optional repeated-bilayer metadata.
         """
 
         sequence = self.layer_sequence_bottom_up()
@@ -140,12 +151,21 @@ def _schematic_layers_and_summary(
             )
             summary_lines.append(f"{self.n_bilayers} bilayers")
             summary_lines.append(f"Bilayer period: {self.d_period_nm:.3f} nm")
-            return layers_top_down, summary_lines
+            return (
+                layers_top_down,
+                summary_lines,
+                _SchematicRepeatUnit(
+                    layer_start_index_top_down=len(layers_top_down) - 2,
+                    bilayer_count=self.n_bilayers,
+                    bilayer_period_nm=self.d_period_nm,
+                    materials_bottom_up=(bottom_material, top_material),
+                ),
+            )
 
         layers_top_down = list(reversed(sequence))
         if max_layers is not None and max_layers > 0:
             layers_top_down = layers_top_down[:max_layers]
-        return layers_top_down, summary_lines
+        return layers_top_down, summary_lines, None
 
     def plot_schematic(
         self,
@@ -161,7 +181,9 @@ def plot_schematic(
                 the uppermost ``max_layers`` are shown.
         """
 
-        layers_top_down, summary_lines = self._schematic_layers_and_summary(max_layers=max_layers)
+        layers_top_down, summary_lines, repeat_unit = self._schematic_layers_and_summary(
+            max_layers=max_layers
+        )
 
         material_labels = self.plot_material_names()
         color_map = {
@@ -179,6 +201,7 @@ def plot_schematic(
         figure, axis = plt.subplots(figsize=(7, figure_height))
 
         current_top_nm = 0.0
+        layer_boundaries_nm = [current_top_nm]
         for material, thickness_nm in layers_top_down:
             label = material_label(material)
             axis.barh(
@@ -199,6 +222,49 @@ def plot_schematic(
                 fontsize=8,
             )
             current_top_nm += thickness_nm
+            layer_boundaries_nm.append(current_top_nm)
+
+        if repeat_unit is not None:
+            top_nm = layer_boundaries_nm[repeat_unit.layer_start_index_top_down]
+            bottom_nm = layer_boundaries_nm[repeat_unit.layer_start_index_top_down + 2]
+            bracket_x = 1.03
+            cap_start_x = 0.98
+            axis.plot(
+                [bracket_x, bracket_x],
+                [top_nm, bottom_nm],
+                color="black",
+                linewidth=1.1,
+                clip_on=False,
+            )
+            axis.plot(
+                [cap_start_x, bracket_x],
+                [top_nm, top_nm],
+                color="black",
+                linewidth=1.1,
+                clip_on=False,
+            )
+            axis.plot(
+                [cap_start_x, bracket_x],
+                [bottom_nm, bottom_nm],
+                color="black",
+                linewidth=1.1,
+                clip_on=False,
+            )
+            bottom_label, top_label = (
+                material_label(material) for material in repeat_unit.materials_bottom_up
+            )
+            axis.text(
+                1.07,
+                0.5 * (top_nm + bottom_nm),
+                (
+                    f"{bottom_label} / {top_label} repeat × {repeat_unit.bilayer_count}\n"
+                    f"Λ = {repeat_unit.bilayer_period_nm:.3f} nm"
+                ),
+                ha="left",
+                va="center",
+                fontsize=8,
+                clip_on=False,
+            )
 
         substrate_thickness_nm = max(10.0, 0.08 * max(current_top_nm, 1.0))
         axis.barh(
@@ -453,7 +519,7 @@ def _schematic_layers_and_summary(
         self,
         *,
         max_layers: int | None = None,
-    ) -> tuple[list[tuple[Any, float]], list[str]]:
+    ) -> tuple[list[tuple[Any, float]], list[str], _SchematicRepeatUnit | None]:
         """Return schematic layers and summary lines for custom stacks.
 
         Multilayer-like repeated bilayer regions are collapsed to one
@@ -482,7 +548,16 @@ def _schematic_layers_and_summary(
 
         summary_lines.append(f"{bilayer_count} bilayers")
         summary_lines.append(f"Bilayer period: {bilayer_period_nm:.3f} nm")
-        return layers_top_down, summary_lines
+        return (
+            layers_top_down,
+            summary_lines,
+            _SchematicRepeatUnit(
+                layer_start_index_top_down=len(explicit_layers_above),
+                bilayer_count=bilayer_count,
+                bilayer_period_nm=bilayer_period_nm,
+                materials_bottom_up=(repeated_layers[0][0], repeated_layers[1][0]),
+            ),
+        )
 
     @staticmethod
     def _detect_repeated_bilayer_block(
diff --git a/src/grax/web/app.py b/src/grax/web/app.py
index 04e577c..74264bc 100644
--- a/src/grax/web/app.py
+++ b/src/grax/web/app.py
@@ -34,6 +34,7 @@
     make_subplots = None
 
 from grax.materials import available_material_symbols, material_density_catalog, material_density_g_cm3
+from grax.simulation.core import normalize_polarization
 
 from .persistence import GratingStore, build_grating_from_spec
 from .runs import RunStore
@@ -886,6 +887,7 @@ def _queue_run(
     diffraction_order = int(float(form.get("diffraction_order", 1)))
     fourier_orders = int(float(form.get("fourier_orders", 5)))
     polarization = _normalized_polarization(form.get("polarization", "s"))
+    solver = _normalized_solver(form.get("solver", "rcwa"))
     worker_mode, max_workers_setting, requested_workers = _worker_settings_from_form(form)
     manifest: dict[str, Any] = {
         "id": run_id,
@@ -897,6 +899,7 @@ def _queue_run(
         "display_name": f"{grating_name} · {workflow}",
         "comment": str(form.get("comment", "")).strip(),
         "polarization": polarization,
+        "solver": solver,
         "status": "queued",
         "artifacts": [],
         "worker_mode": worker_mode,
@@ -1058,6 +1061,7 @@ def _execute_run_job(
                 grazing_angle_deg=float(form_data["grazing_angle_deg"]),
                 diffraction_order=diffraction_order,
                 polarization=_normalized_polarization(form_data.get("polarization", "s")),
+                solver=_normalized_solver(form_data.get("solver", "rcwa")),
                 fourier_orders_values=[fourier_orders],
                 x_resolution_values=[run_x_resolution_nm],
                 z_resolution_values=[run_z_resolution_nm],
@@ -1094,8 +1098,9 @@ def _execute_run_job(
             fourier_orders=fourier_orders,
         )
         runner = simulation.BatchSimulationRunner(
-            default_diffraction_order=diffraction_order,
-            default_fourier_orders=fourier_orders,
+            diffraction_order=diffraction_order,
+            fourier_orders=fourier_orders,
+            solver=_normalized_solver(form_data.get("solver", "rcwa")),
             max_workers=effective_max_workers,
             show_progress=False,
             on_error="continue",
@@ -1240,16 +1245,28 @@ def _run_input_from_form(form: Any) -> dict[str, Any]:
         values = form.getlist(key)
         input_data[key] = values if len(values) > 1 else form.get(key)
     input_data["polarization"] = _normalized_polarization(input_data.get("polarization", "s"))
+    input_data["solver"] = _normalized_solver(input_data.get("solver", "rcwa"))
     return input_data
 
 
 def _normalized_polarization(value: Any) -> str:
-    """Return a validated polarization code for Web UI run inputs."""
+    """Return a canonical polarization code for Web UI run inputs.
+
+    Delegates to :func:`grax.normalize_polarization`, so the form accepts the
+    same ``TE``/``TM`` aliases the Python API does and stores the canonical
+    ``"s"``/``"p"``.
+    """
+
+    return normalize_polarization(value or "s")
+
+
+def _normalized_solver(value: Any) -> str:
+    """Return a validated electromagnetic solver name for Web UI run inputs."""
 
-    polarization = str(value or "s").strip().lower()
-    if polarization not in {"s", "p"}:
-        raise ValueError("polarization must be 's' or 'p'.")
-    return polarization
+    solver = str(value or "rcwa").strip().lower()
+    if solver not in {"rcwa", "neviere"}:
+        raise ValueError("solver must be 'rcwa' or 'neviere'.")
+    return solver
 
 
 def _request_run_abort(app: Any, data_dir: Path, run_id: str, *, delete_after_abort: bool) -> bool:
@@ -1521,6 +1538,7 @@ def _load_run_manifest(data_dir: Path, run_id: str) -> dict[str, Any] | None:
     payload.setdefault("id", run_id)
     payload.setdefault("display_name", f"{payload.get('grating_name', 'Run')} · {payload.get('workflow', 'run')}")
     payload.setdefault("polarization", _normalized_polarization(payload.get("run_input", {}).get("polarization", "s")))
+    payload.setdefault("solver", _normalized_solver(payload.get("run_input", {}).get("solver", "rcwa")))
     if isinstance(payload.get("run_input"), dict):
         payload["run_input"].setdefault("polarization", payload["polarization"])
     return payload
diff --git a/src/grax/web/templates/grating_detail.html b/src/grax/web/templates/grating_detail.html
index 653f08d..0ce284a 100644
--- a/src/grax/web/templates/grating_detail.html
+++ b/src/grax/web/templates/grating_detail.html
@@ -64,8 +64,14 @@ <h1>{{ grating.name }}</h1>
     <label>Fourier orders <input name="fourier_orders" type="number" step="1" value="5"></label>
     <label>Polarization
       <select name="polarization">
-        <option value="s" selected>s</option>
-        <option value="p">p</option>
+        <option value="s" selected>s (TE)</option>
+        <option value="p">p (TM)</option>
+      </select>
+    </label>
+    <label>Solver
+      <select name="solver">
+        <option value="rcwa" selected>RCWA (modal)</option>
+        <option value="neviere">Nevi&egrave;re (differential)</option>
       </select>
     </label>
     <label>Roughness
diff --git a/src/grax/web/templates/run_detail.html b/src/grax/web/templates/run_detail.html
index 4e28571..940253c 100644
--- a/src/grax/web/templates/run_detail.html
+++ b/src/grax/web/templates/run_detail.html
@@ -23,6 +23,10 @@ <h1>{{ run.display_name | default(run.workflow, true) }}</h1>
   <p>
     This run is saved in <code>{{ run.results_dir }}</code>.
   </p>
+  <p>
+    Solver: <code>{{ run.solver | default('rcwa', true) }}</code> &middot;
+    Polarization: <code>{{ run.polarization | default('s', true) }}</code>
+  </p>
 </section>
 
 <section
diff --git a/src/grax/web/templates/web_docs.html b/src/grax/web/templates/web_docs.html
index 2466580..d794b27 100644
--- a/src/grax/web/templates/web_docs.html
+++ b/src/grax/web/templates/web_docs.html
@@ -81,7 +81,14 @@ <h2>Run simulations</h2>
   <ol>
     <li>Open a saved grating from the home page.</li>
     <li>Pick a workflow: fixed angle, monochromator, multilayer theta search, or parameter study.</li>
-    <li>Enter the energy range, diffraction order, Fourier orders, polarization, and any workflow-specific values.</li>
+    <li>Enter the energy range, diffraction order, Fourier orders, polarization (<code>s</code> is TE, <code>p</code> is TM), and any workflow-specific values.</li>
+    <li>
+      Pick the solver. <strong>RCWA</strong> is the default modal solver, inspired
+      by RETICOLO. <strong>Nevi&egrave;re</strong> is the differential method. Both
+      paths share the same grating and workflow inputs but propagate through the
+      grating differently; the saved run records which one produced it. Nevi&egrave;re
+      stays stable on gratings far deeper than modal RCWA can handle.
+    </li>
     <li>Add an optional run comment if you want the saved run to carry a note or experiment tag.</li>
     <li>Choose the worker mode if you want auto or manual multiprocessing.</li>
     <li>Run the sweep and follow the progress page while the simulation writes results.</li>
diff --git a/src/grax_opt/dynamic.py b/src/grax_opt/dynamic.py
index 4aa57c6..3476f8c 100644
--- a/src/grax_opt/dynamic.py
+++ b/src/grax_opt/dynamic.py
@@ -172,6 +172,12 @@ class MeasurementFitConfig:
         save_best_fit_plot: Whether to write ``best_fit.png``.
         save_loss_plot: Whether to write ``optimization_loss_history.png``.
         backend: Requested compute backend.
+        solver: Electromagnetic solver used for every trial evaluation,
+            ``"rcwa"`` (default) or ``"neviere"``. Unlike ``backend`` there is no
+            ``"auto"`` mode: the two solvers are different methods, not
+            interchangeable implementations of one.
+        solver_options: Integration settings for ``solver="neviere"``, as a
+            mapping matching :class:`grax.NeviereOptions`.
         evaluation_energies_ev: Discrete energies used for objective evaluation.
         evaluation_grazing_angles_deg: Optional grazing angles (deg) used for
             explicit energy-angle evaluation pairs.
@@ -207,6 +213,8 @@ class MeasurementFitConfig:
     save_best_fit_plot: bool = True
     save_loss_plot: bool = True
     backend: str = "auto"
+    solver: str = "rcwa"
+    solver_options: dict[str, object] | None = None
     evaluation_energies_ev: list[float] = field(default_factory=list)
     evaluation_grazing_angles_deg: list[float] = field(default_factory=list)
     max_workers: int | str | None = None
@@ -269,6 +277,8 @@ def __post_init__(self) -> None:
             raise ValueError("early_stopping_warmup_trials must be >= 0.")
         if self.backend not in {"auto", "numba", "numpy"}:
             raise ValueError("backend must be one of: auto, numba, numpy.")
+        if self.solver not in {"rcwa", "neviere"}:
+            raise ValueError("solver must be one of: rcwa, neviere.")
         selection = normalize_evaluation_selection(
             self.evaluation_energies_ev,
             self.evaluation_grazing_angles_deg,
@@ -343,6 +353,8 @@ def from_mapping(cls, mapping: Mapping[str, object]) -> "MeasurementFitConfig":
             save_best_fit_plot=config.pop("save_best_fit_plot", True),
             save_loss_plot=config.pop("save_loss_plot", True),
             backend=config.pop("backend", "auto"),
+            solver=config.pop("solver", "rcwa"),
+            solver_options=config.pop("solver_options", None),
             evaluation_energies_ev=list(config.pop("evaluation_energies_ev", [])),
             evaluation_grazing_angles_deg=list(
                 config.pop("evaluation_grazing_angles_deg", [])
@@ -544,6 +556,8 @@ def _write_measurement_fit_result_json(
         "early_stop_reason": early_stop_reason,
         "backend_requested": backend_requested,
         "backend_effective": backend_effective,
+        "solver": str(getattr(config, "solver", "rcwa")),
+        "solver_options": getattr(config, "solver_options", None),
         "optimizer_execution_strategy": "trial_batch_runner",
         "optimizer_requested_max_workers": optimizer_requested_max_workers,
         "optimizer_resolved_max_workers": int(optimizer_resolved_max_workers),
diff --git a/src/grax_opt/objective.py b/src/grax_opt/objective.py
index 25df687..0d62826 100644
--- a/src/grax_opt/objective.py
+++ b/src/grax_opt/objective.py
@@ -124,7 +124,7 @@ def simulate_efficiency_curve_with_metadata(
         config: Optimization configuration describing the simulation setup.
         trial_parameters: Ax trial parameters for the current candidate.
         measurement: Energy grid and target efficiencies used for evaluation.
-        backend: RCWA backend to use for the simulation.
+        backend: Fourier coefficient backend to use for the simulation.
         build_grating_fn: Optional hook that builds a grating from the trial
             parameter mapping.
         resolve_solver_parameters_fn: Optional hook that resolves solver
@@ -132,6 +132,12 @@ def simulate_efficiency_curve_with_metadata(
 
     Returns:
         Simulated efficiency values on the measurement grid.
+
+    Note:
+        The electromagnetic solver comes from ``config.solver`` (and
+        ``config.solver_options``), alongside ``diffraction_order`` and
+        ``fourier_orders``, rather than from a separate argument. ``backend``
+        stays an argument because it is resolved from ``"auto"`` by the caller.
     """
 
     if build_grating_fn is None:
@@ -162,11 +168,13 @@ def simulate_efficiency_curve_with_metadata(
         )
 
     runner = BatchSimulationRunner(
-        default_diffraction_order=int(config.diffraction_order),
-        default_fourier_orders=int(config.fourier_orders),
+        diffraction_order=int(config.diffraction_order),
+        fourier_orders=int(config.fourier_orders),
         max_workers=getattr(config, "max_workers", None),
         validate_physical_results=bool(config.validate_physical_results),
         backend=backend,
+        solver=str(getattr(config, "solver", "rcwa")),
+        solver_options=getattr(config, "solver_options", None),
     )
     trial_results = list(runner.run_cases(cases))
     efficiencies = np.empty(len(cases), dtype=float)
diff --git a/tests/simulation_helpers.py b/tests/simulation_helpers.py
index 188d7c9..3353f9e 100644
--- a/tests/simulation_helpers.py
+++ b/tests/simulation_helpers.py
@@ -32,6 +32,10 @@
     Path(__file__).resolve().parents[1] / "examples" / "simulation" / "batch_user_cases" / "batch_user_cases.py",
     Path(__file__).resolve().parents[1] / "examples" / "simulation" / "blazed_multilayer_sweep" / "blazed_multilayer_sweep.py",
     Path(__file__).resolve().parents[1] / "examples" / "simulation" / "blazed_multilayer_memory_comparison" / "blazed_multilayer_memory_comparison.py",
+    Path(__file__).resolve().parents[1] / "examples" / "simulation" / "neviere_solver" / "neviere_solver.py",
+    Path(__file__).resolve().parents[1] / "examples" / "simulation" / "deep_grating_limits" / "deep_grating_limits.py",
+    Path(__file__).resolve().parents[1] / "examples" / "simulation" / "continuous_vs_staircase" / "continuous_vs_staircase.py",
+    Path(__file__).resolve().parents[1] / "examples" / "simulation" / "solver_runtime" / "solver_runtime.py",
 ]
 OPTIMIZER_EXAMPLE_ROOT = (
     Path(__file__).resolve().parents[1] / "examples" / "optimizer" / "optimizer_laminar"
diff --git a/tests/smoke/test_neviere_solver.py b/tests/smoke/test_neviere_solver.py
new file mode 100644
index 0000000..97d3275
--- /dev/null
+++ b/tests/smoke/test_neviere_solver.py
@@ -0,0 +1,161 @@
+"""End-to-end checks for the Nevière differential-method solver.
+
+These use the published RETICOLO ``exemple1_1D.m`` configuration already
+referenced by ``test_simulation_reticolo_parity``: a deep, high-contrast
+lamellar grating at normal incidence. It is a much harder convergence case than
+the shallow X-ray gratings the project normally runs, and it exercises both the
+TM fast-Fourier-factorization rules and the stability of the interface-response
+cascade across many wavelengths of optical thickness.
+"""
+
+from __future__ import annotations
+
+import numpy as np
+import pytest
+
+from grax.solvers import res0, res1, res2, res2_dm
+from grax.solvers.neviere import NeviereOptions
+
+# lambda = 6 um, period = 10 um, 20 um deep, n = 1.5 ridges over [0, 1] and
+# [9, 10] um with n = 1 grooves between, normal incidence, 25 Fourier orders.
+_WAVELENGTH_NM = 6000.0
+_PERIOD_NM = 10000.0
+_DEPTH_NM = 20000.0
+_FOURIER_ORDERS = 25
+_GRATING_TEXTURE = [
+    np.array([1000.0, 9000.0]),
+    np.array([1.5, 1.0], dtype=complex),
+]
+
+# Published RETICOLO exemple1_1D.m zeroth-order transmission.
+_RETICOLO_TRANSMISSION = {1: 0.5050632035, -1: 0.9111790287}
+
+
+def _solve(polarization: int, *, depth_nm: float = _DEPTH_NM, solver: str = "neviere",
+           options: NeviereOptions | None = None):
+    """Return the zeroth-order transmission and the total energy for one solve."""
+
+    parm = res0(polarization)
+    aa = res1(
+        _WAVELENGTH_NM,
+        _PERIOD_NM,
+        [1.0, 1.5, _GRATING_TEXTURE],
+        _FOURIER_ORDERS,
+        0.0,
+        parm,
+        _fourier_backend="numba",
+    )
+    profile = ([0.0, depth_nm, 0.0], [0, 2, 1])
+    if solver == "rcwa":
+        result = res2(aa, profile, parm)
+    else:
+        result = res2_dm(aa, profile, parm, options=options)
+
+    zeroth_index = int(np.where(result.inc_top_reflected.order == 0)[0][0])
+    transmission = float(result.inc_top_transmitted.efficiency[zeroth_index])
+    total = float(
+        np.sum(result.inc_top_reflected.efficiency)
+        + np.sum(result.inc_top_transmitted.efficiency)
+    )
+    return transmission, total, result
+
+
+@pytest.mark.smoke
+@pytest.mark.parametrize(
+    ("polarization", "label"),
+    [(1, "TE"), (-1, "TM")],
+)
+def test_neviere_matches_published_reticolo_lamellar_reference(
+    polarization: int,
+    label: str,
+) -> None:
+    """Verify the differential method reproduces the published RETICOLO values.
+
+    TM is the load-bearing case: without the Li/fast-Fourier-factorization
+    inverse rule a differential-method solve of this high-contrast profile
+    converges far too slowly to reach this agreement at 25 orders.
+    """
+
+    transmission, total, _ = _solve(polarization)
+
+    assert transmission == pytest.approx(_RETICOLO_TRANSMISSION[polarization], abs=1e-6), label
+    assert total == pytest.approx(1.0, abs=1e-6)
+
+
+@pytest.mark.smoke
+@pytest.mark.parametrize("polarization", [1, -1])
+def test_neviere_agrees_with_rcwa_on_the_lamellar_reference(polarization: int) -> None:
+    """Verify both solvers land on the same answer for the reference geometry."""
+
+    neviere_transmission, _, neviere = _solve(polarization)
+    rcwa_transmission, _, rcwa = _solve(polarization, solver="rcwa")
+
+    assert neviere_transmission == pytest.approx(rcwa_transmission, abs=1e-9)
+    assert np.allclose(
+        np.real(neviere.inc_top_reflected.efficiency),
+        np.real(rcwa.inc_top_reflected.efficiency),
+        atol=1e-9,
+    )
+    assert np.allclose(
+        np.real(neviere.inc_top_transmitted.efficiency),
+        np.real(rcwa.inc_top_transmitted.efficiency),
+        atol=1e-9,
+    )
+
+
+@pytest.mark.smoke
+@pytest.mark.parametrize("polarization", [1, -1])
+def test_neviere_agrees_with_rcwa_at_the_deepest_shared_depth(polarization: int) -> None:
+    """Verify the solvers still agree just below the modal solver's depth ceiling.
+
+    The modal solver overflows above roughly 7 wavelengths of depth for this
+    high-contrast profile (TE first, TM shortly after), so this is close to the
+    deepest structure the two can be compared on directly.
+    """
+
+    depth_nm = 40000.0
+    neviere_transmission, neviere_total, _ = _solve(polarization, depth_nm=depth_nm)
+    rcwa_transmission, _, _ = _solve(polarization, depth_nm=depth_nm, solver="rcwa")
+
+    assert neviere_transmission == pytest.approx(rcwa_transmission, abs=1e-8)
+    assert neviere_total == pytest.approx(1.0, abs=1e-6)
+
+
+@pytest.mark.smoke
+@pytest.mark.parametrize("polarization", [1, -1])
+def test_neviere_stays_stable_far_beyond_the_rcwa_depth_ceiling(polarization: int) -> None:
+    """Verify very deep gratings stay finite and energy-conserving.
+
+    At 167 wavelengths the evanescent orders span hundreds of e-foldings. The
+    modal solver forms ``q / sinh(q d)`` across the whole layer in one go and
+    overflows well before this depth; the differential method only ever forms a
+    transfer matrix across a sub-block bounded by ``block_phase`` and combines
+    those with the interface-response cascade, which is an R-matrix propagation
+    and never builds a growing exponential.
+    """
+
+    depth_nm = 1.0e6
+    transmission, total, result = _solve(polarization, depth_nm=depth_nm)
+
+    assert np.all(np.isfinite(np.real(result.inc_top_reflected.efficiency)))
+    assert np.all(np.isfinite(np.real(result.inc_top_transmitted.efficiency)))
+    assert 0.0 <= transmission <= 1.0
+    assert total == pytest.approx(1.0, abs=1e-6)
+
+    # Guards the premise: the modal solver genuinely cannot reach this depth, so
+    # if it ever gains the range this test should be revisited rather than kept
+    # as a claimed differential-method advantage.
+    with pytest.raises(ValueError, match="NaN/Inf"):
+        _solve(polarization, depth_nm=depth_nm, solver="rcwa")
+
+
+@pytest.mark.smoke
+def test_neviere_reference_is_insensitive_to_the_sub_block_size() -> None:
+    """Verify block_phase only trades conditioning, not the converged answer."""
+
+    transmissions = [
+        _solve(-1, options=NeviereOptions(block_phase=block_phase))[0]
+        for block_phase in (4.0, 2.0, 1.0, 0.5)
+    ]
+
+    assert np.allclose(transmissions, transmissions[0], atol=1e-9)
diff --git a/tests/smoke/test_simulation_examples.py b/tests/smoke/test_simulation_examples.py
index 9525ca1..609a216 100644
--- a/tests/smoke/test_simulation_examples.py
+++ b/tests/smoke/test_simulation_examples.py
@@ -170,7 +170,7 @@ def test_single_simulation_example_parity_quick_configuration(tmp_path: Path) ->
 def test_fixed_angle_example_parity_quick_configuration(tmp_path: Path) -> None:
     grating = build_laminar_example_grating(x_resolution_nm=1.0, z_resolution_nm=1.0)
     cases = fixed_angle_cases(grating=grating, energies_ev=[200.0], grazing_angle_deg=4.0)
-    runner = BatchSimulationRunner(default_diffraction_order=1, default_fourier_orders=3)
+    runner = BatchSimulationRunner(diffraction_order=1, fourier_orders=3)
     results = list(runner.run_cases(cases))
     csv_path = tmp_path / "fixed_angle_all_orders.csv"
     orders_plot_path = tmp_path / "fixed_angle_orders_1_3.png"
@@ -187,7 +187,7 @@ def test_fixed_angle_example_parity_quick_configuration(tmp_path: Path) -> None:
 def test_monochromator_example_parity_quick_configuration(tmp_path: Path) -> None:
     grating = build_monochromator_example_grating(x_resolution_nm=1.0, z_resolution_nm=1.0)
     cases = monochromator_cases(grating=grating, energies_ev=[200.0], diffraction_order=1, cff=2.25)
-    runner = BatchSimulationRunner(default_fourier_orders=3)
+    runner = BatchSimulationRunner(fourier_orders=3)
     results = list(runner.run_cases(cases))
     csv_path = tmp_path / "monochromator_all_orders.csv"
     orders_plot_path = tmp_path / "monochromator_orders_1_3.png"
@@ -219,7 +219,7 @@ def test_blazed_multilayer_sweep_example_parity_quick_configuration(tmp_path: Pa
         z_resolution_nm=1.0,
     )
     cases = monochromator_cases(grating=grating, energies_ev=[500.0], diffraction_order=1, cff=2.25)
-    runner = BatchSimulationRunner(default_diffraction_order=1, default_fourier_orders=3)
+    runner = BatchSimulationRunner(diffraction_order=1, fourier_orders=3)
     results = list(runner.run_cases(cases))
     csv_path = tmp_path / "blazed_multilayer_all_orders.csv"
 
@@ -251,8 +251,10 @@ def test_blazed_multilayer_memory_comparison_example_structure() -> None:
     assert '"memory_mode"' not in source
     assert '"_memory_mode"' not in source
     assert 'profile_memory": True' in source
-    assert "blazed_multilayer_memory_comparison.csv" in source
-    assert "blazed_multilayer_memory_comparison.png" in source
+    # Outputs are solver-suffixed so an rcwa and a neviere run sit side by side.
+    assert 'blazed_multilayer_memory_comparison_{args.solver}.csv' in source
+    assert 'blazed_multilayer_memory_comparison_{args.solver}.png' in source
+    assert '"--solver"' in source
     assert "blazed_multilayer_profile.png" in source
     assert "multilayer_stack_schematic.png" in source
 
@@ -260,7 +262,7 @@ def test_blazed_multilayer_memory_comparison_example_structure() -> None:
 def test_energy_angle_example_parity_quick_configuration(tmp_path: Path) -> None:
     grating = build_blazed_multilayer_angle_parity_grating()
     cases = energy_angle_cases(grating=grating, energy_angle_pairs=[(1800.0, 8.0)])
-    runner = BatchSimulationRunner(default_diffraction_order=2, default_fourier_orders=3)
+    runner = BatchSimulationRunner(diffraction_order=2, fourier_orders=3)
     results = list(runner.run_cases(cases))
     csv_path = tmp_path / "energy_angle_all_orders.csv"
 
@@ -331,7 +333,7 @@ def test_batch_user_cases_example_parity_quick_configuration(tmp_path: Path) ->
             "depth_nm": 14.9,
         }
     ]
-    runner = BatchSimulationRunner(default_diffraction_order=1, default_fourier_orders=3)
+    runner = BatchSimulationRunner(diffraction_order=1, fourier_orders=3)
     results = list(runner.run_cases(user_cases))
     csv_path = tmp_path / "batch_user_cases_all_orders.csv"
 
diff --git a/tests/smoke/test_simulation_reticolo_parity.py b/tests/smoke/test_simulation_reticolo_parity.py
index ef78fbc..5bc261a 100644
--- a/tests/smoke/test_simulation_reticolo_parity.py
+++ b/tests/smoke/test_simulation_reticolo_parity.py
@@ -33,7 +33,7 @@
     BatchSimulationRunner,
     CaseExecutionResult,
     MultilayerThetaSearchSweepResult,
-    RCWASimulation,
+    GratingSimulation,
     SingleSimulationResult,
     energy_angle_cases,
     estimate_multilayer_bragg_angle_deg,
@@ -118,7 +118,7 @@ def test_laminar_multilayer_material_map_matches_octave_reference(tmp_path: Path
 def test_laminar_multilayer_solver_matches_octave_reference(tmp_path: Path) -> None:
     octave_reference = run_octave_laminar_multilayer_reference(tmp_path)
     grating = build_multilayer_parity_grating()
-    simulation = RCWASimulation(
+    simulation = GratingSimulation(
         grating=grating,
         diffraction_order=1,
         fourier_orders=5,
@@ -149,7 +149,7 @@ def test_laminar_multilayer_solver_stays_physical_for_full_example(tmp_path: Pat
         fourier_orders=5,
     )
     grating = build_multilayer_solver_regression_grating()
-    simulation = RCWASimulation(
+    simulation = GratingSimulation(
         grating=grating,
         diffraction_order=1,
         fourier_orders=5,
@@ -178,7 +178,7 @@ def test_blazed_multilayer_angle_sweep_matches_reticolo_v9_reference(tmp_path: P
     expected_reticolo_orders = np.arange(-5, 2, dtype=int)
 
     for grazing_angle_deg in np.arange(75, 82, dtype=float) / 10.0:
-        simulation = RCWASimulation(
+        simulation = GratingSimulation(
             grating=grating,
             diffraction_order=1,
             fourier_orders=5,
@@ -218,7 +218,7 @@ def test_blazed_single_layer_200ev_matches_reticolo_reference_more_closely() ->
             cff=2.25,
         )[0]
     )
-    simulation = RCWASimulation(
+    simulation = GratingSimulation(
         grating=grating,
         diffraction_order=1,
         fourier_orders=20,
diff --git a/tests/unit/test_afm.py b/tests/unit/test_afm.py
index ae2839d..490d697 100644
--- a/tests/unit/test_afm.py
+++ b/tests/unit/test_afm.py
@@ -302,7 +302,7 @@ def test_afm_grating_runs_in_batch_case_path() -> None:
         x_resolution_nm=4.0,
         z_resolution_nm=2.0,
     )
-    runner = BatchSimulationRunner(default_fourier_orders=3, show_progress=False)
+    runner = BatchSimulationRunner(fourier_orders=3, show_progress=False)
     cases = [{"grating": grating, "energy_ev": 500.0, "grazing_angle_deg": 4.0}]
     results = list(runner.run_cases(cases))
     assert len(results) == 1
diff --git a/tests/unit/test_gratings.py b/tests/unit/test_gratings.py
index c44a235..4912ec8 100644
--- a/tests/unit/test_gratings.py
+++ b/tests/unit/test_gratings.py
@@ -539,7 +539,7 @@ def test_custom_stack_schematic_collapses_repeated_bilayers() -> None:
         top_cap_thickness_nm=2.0,
     )
 
-    layers_top_down, summary_lines = stack._schematic_layers_and_summary()
+    layers_top_down, summary_lines, repeat_unit = stack._schematic_layers_and_summary()
 
     assert [material_label(material) for material, _ in layers_top_down] == ["O", "C", "Cr", "Cr"]
     assert [thickness for _, thickness in layers_top_down] == pytest.approx([2.0, 3.6, 2.4, 2.0])
@@ -548,6 +548,11 @@ def test_custom_stack_schematic_collapses_repeated_bilayers() -> None:
         "3 bilayers",
         "Bilayer period: 6.000 nm",
     ]
+    assert repeat_unit is not None
+    assert repeat_unit.layer_start_index_top_down == 1
+    assert repeat_unit.bilayer_count == 3
+    assert repeat_unit.bilayer_period_nm == pytest.approx(6.0)
+    assert [material_label(material) for material in repeat_unit.materials_bottom_up] == ["Cr", "C"]
 
 
 def test_custom_stack_schematic_keeps_literal_nonrepeating_layers() -> None:
@@ -560,11 +565,38 @@ def test_custom_stack_schematic_keeps_literal_nonrepeating_layers() -> None:
         ],
     )
 
-    layers_top_down, summary_lines = stack._schematic_layers_and_summary()
+    layers_top_down, summary_lines, repeat_unit = stack._schematic_layers_and_summary()
 
     assert [material_label(material) for material, _ in layers_top_down] == ["Cr", "C", "Pt"]
     assert [thickness for _, thickness in layers_top_down] == pytest.approx([1.0, 2.0, 10.0])
     assert summary_lines == ["Total thickness: 13.000 nm"]
+    assert repeat_unit is None
+
+
+def test_multilayer_stack_schematic_marks_native_bilayer_repeat() -> None:
+    stack = MultilayerStack(
+        substrate_material=SI,
+        material_a=CR,
+        material_b=C,
+        d_period_nm=6.0,
+        gamma=0.4,
+        n_bilayers=50,
+        top_material=C,
+    )
+
+    layers_top_down, summary_lines, repeat_unit = stack._schematic_layers_and_summary()
+
+    assert [material_label(material) for material, _ in layers_top_down] == ["C", "Cr"]
+    assert summary_lines == [
+        "Total thickness: 300.000 nm",
+        "50 bilayers",
+        "Bilayer period: 6.000 nm",
+    ]
+    assert repeat_unit is not None
+    assert repeat_unit.layer_start_index_top_down == 0
+    assert repeat_unit.bilayer_count == 50
+    assert repeat_unit.bilayer_period_nm == pytest.approx(6.0)
+    assert [material_label(material) for material in repeat_unit.materials_bottom_up] == ["Cr", "C"]
 
 
 def test_stack_builder_helpers_match_existing_stack_types() -> None:
diff --git a/tests/unit/test_neviere.py b/tests/unit/test_neviere.py
new file mode 100644
index 0000000..88b25e4
--- /dev/null
+++ b/tests/unit/test_neviere.py
@@ -0,0 +1,1146 @@
+"""Unit tests for the Nevière differential-method solver."""
+
+from __future__ import annotations
+
+import dataclasses
+import json
+import warnings
+from pathlib import Path
+
+import numpy as np
+import pytest
+
+import grax
+from grax import rcwa_1d
+from grax.gratings import BlazedGrating, LaminarGrating, ProfileGrating
+from grax.simulation import (
+    BatchSimulationRunner,
+    energy_angle_cases,
+    fixed_angle_cases,
+    monochromator_cases,
+    multilayer_theta_search_cases,
+    run_multilayer_theta_search,
+    run_simulation,
+)
+from grax.simulation.serialization import _case_result_from_record
+from grax.solvers import res0, res1, res2, res2_dm
+from grax.solvers.common import prepare_layer_stack, propagating_energy_balance
+from grax.solvers.neviere import (
+    NeviereOptions,
+    build_grating_epsilon_sampler,
+    coerce_neviere_options,
+)
+from grax.stacks import MultilayerStack
+from tests.optical_constants import OpticalConstantsTable
+from tests.simulation_helpers import AU, C, CR, PT, SI
+
+# A purely real refractive index (beta = 0) so the structure is lossless and the
+# propagating orders must sum to exactly one.
+LOSSLESS = OpticalConstantsTable(
+    energy_ev=np.asarray([1.0, 1.0e5], dtype=float),
+    delta=np.asarray([0.02, 0.02], dtype=float),
+    beta=np.zeros(2, dtype=float),
+    name="LosslessDielectric",
+)
+LOSSLESS_INDEX = 1.0 - 0.02
+
+# Deviations between the two solvers are pure Runge-Kutta truncation error and
+# measure ~1e-11 at production resolution; these bounds sit well above that
+# noise floor while still catching any real divergence.
+SOLVER_PARITY_ATOL = 1e-8
+SOLVER_PARITY_RTOL = 1e-6
+
+
+def _laminar_grating() -> LaminarGrating:
+    """Return a coarse coated laminar grating."""
+
+    return LaminarGrating(
+        period_lpermm=400,
+        width_to_period_ratio=0.67,
+        depth_nm=14.9,
+        left_wall_angle_deg=15.0,
+        right_wall_angle_deg=15.0,
+        substrate_material=SI,
+        layer_material=PT,
+        layer_thickness_nm=28.77,
+        top_cap_material=C,
+        top_cap_thickness_nm=0.7,
+        x_resolution_nm=4.0,
+        z_resolution_nm=1.0,
+    )
+
+
+def _blazed_grating() -> BlazedGrating:
+    """Return a coarse coated blazed grating."""
+
+    return BlazedGrating(
+        period_lpermm=600,
+        blaze_angle_deg=0.729,
+        anti_blaze_angle_deg=5.597,
+        substrate_material=SI,
+        layer_material=AU,
+        layer_thickness_nm=30.0,
+        x_resolution_nm=4.0,
+        z_resolution_nm=1.0,
+    )
+
+
+def _multilayer_grating() -> BlazedGrating:
+    """Return a coarse blazed grating on a Cr/C multilayer stack."""
+
+    return BlazedGrating(
+        period_lpermm=2400,
+        blaze_angle_deg=1.37,
+        anti_blaze_angle_deg=3.25,
+        coating_stack=MultilayerStack(
+            substrate_material=SI,
+            material_a=CR,
+            material_b=C,
+            d_period_nm=4.8,
+            gamma=0.4,
+            n_bilayers=8,
+            top_material=C,
+        ),
+        x_resolution_nm=2.0,
+        z_resolution_nm=0.5,
+    )
+
+
+def _sinusoidal_grating(
+    *,
+    depth_nm: float = 10.0,
+    material: object = None,
+    period_lpermm: int = 2000,
+    z_resolution_nm: float = 0.25,
+) -> ProfileGrating:
+    """Return a sinusoidal surface-relief grating built from explicit points."""
+
+    resolved_material = SI if material is None else material
+    period_nm = 1e6 / period_lpermm
+    x_points_nm = np.linspace(0.0, period_nm, 33)
+    z_points_nm = depth_nm * 0.5 * (1.0 - np.cos(2.0 * np.pi * x_points_nm / period_nm))
+    return ProfileGrating(
+        period_lpermm=period_lpermm,
+        x_points_nm=x_points_nm,
+        z_points_nm=z_points_nm,
+        substrate_material=resolved_material,
+        layer_material=resolved_material,
+        layer_thickness_nm=5.0,
+        x_resolution_nm=2.0,
+        z_resolution_nm=z_resolution_nm,
+    )
+
+
+def _solve_pair(
+    grating: object,
+    *,
+    energy_ev: float,
+    grazing_angle_deg: float,
+    polarization: str,
+    fourier_orders: int,
+    options: NeviereOptions | None = None,
+):
+    """Return the reflected/transmitted results from both solvers for one case."""
+
+    parm = res0(1 if polarization == "s" else -1)
+    textures, profile = grating.build_textures(energy_ev, n_inc=1.0 + 0.0j)
+    aa = res1(
+        1239.8 / energy_ev,
+        grating.period_nm,
+        textures,
+        fourier_orders,
+        np.sin(np.deg2rad(90.0 - grazing_angle_deg)),
+        parm,
+        _fourier_backend="numba",
+    )
+    return aa, profile, res2(aa, profile, parm), res2_dm(aa, profile, parm, options=options)
+
+
+def _assert_solvers_agree(
+    grating: object,
+    *,
+    energy_ev: float,
+    grazing_angle_deg: float,
+    polarization: str,
+    fourier_orders: int,
+) -> None:
+    """Assert both solvers return the same all-order efficiencies and angles."""
+
+    common = dict(
+        grating=grating,
+        energy_ev=energy_ev,
+        grazing_angle_deg=grazing_angle_deg,
+        fourier_orders=fourier_orders,
+        polarization=polarization,
+        validate_physical_results=False,
+    )
+    rcwa_result = run_simulation(**common, solver="rcwa")
+    neviere_result = run_simulation(**common, solver="neviere")
+
+    assert np.array_equal(rcwa_result.orders, neviere_result.orders)
+    assert np.allclose(
+        rcwa_result.efficiency_all,
+        neviere_result.efficiency_all,
+        atol=SOLVER_PARITY_ATOL,
+        rtol=SOLVER_PARITY_RTOL,
+    )
+    assert np.allclose(
+        rcwa_result.diffraction_angle_all,
+        neviere_result.diffraction_angle_all,
+        atol=1e-9,
+    )
+    assert rcwa_result.solver == "rcwa"
+    assert neviere_result.solver == "neviere"
+
+
+@pytest.mark.unit
+@pytest.mark.parametrize("polarization", ["s", "p"])
+def test_neviere_matches_rcwa_for_laminar_grating(polarization: str) -> None:
+    """Verify the differential method reproduces RCWA on a coated laminar grating."""
+
+    _assert_solvers_agree(
+        _laminar_grating(),
+        energy_ev=300.0,
+        grazing_angle_deg=4.0,
+        polarization=polarization,
+        fourier_orders=10,
+    )
+
+
+@pytest.mark.unit
+@pytest.mark.parametrize("polarization", ["s", "p"])
+def test_neviere_matches_rcwa_for_blazed_grating(polarization: str) -> None:
+    """Verify the differential method reproduces RCWA on a blazed grating."""
+
+    _assert_solvers_agree(
+        _blazed_grating(),
+        energy_ev=500.0,
+        grazing_angle_deg=1.5,
+        polarization=polarization,
+        fourier_orders=8,
+    )
+
+
+@pytest.mark.unit
+@pytest.mark.parametrize("polarization", ["s", "p"])
+def test_neviere_matches_rcwa_for_sinusoidal_grating(polarization: str) -> None:
+    """Verify the differential method reproduces RCWA on a sinusoidal profile."""
+
+    _assert_solvers_agree(
+        _sinusoidal_grating(),
+        energy_ev=300.0,
+        grazing_angle_deg=5.0,
+        polarization=polarization,
+        fourier_orders=8,
+    )
+
+
+@pytest.mark.unit
+@pytest.mark.parametrize("polarization", ["s", "p"])
+def test_neviere_matches_rcwa_for_multilayer_stack(polarization: str) -> None:
+    """Verify the differential method reproduces RCWA on a blazed multilayer stack."""
+
+    _assert_solvers_agree(
+        _multilayer_grating(),
+        energy_ev=500.0,
+        grazing_angle_deg=14.176,
+        polarization=polarization,
+        fourier_orders=6,
+    )
+
+
+@pytest.mark.unit
+@pytest.mark.parametrize("polarization", ["s", "p"])
+def test_neviere_conserves_energy_for_lossless_dielectric_grating(polarization: str) -> None:
+    """Verify propagating reflected and transmitted orders sum to one without absorption."""
+
+    grating = _sinusoidal_grating(depth_nm=12.0, material=LOSSLESS)
+    aa, profile, _, neviere = _solve_pair(
+        grating,
+        energy_ev=500.0,
+        grazing_angle_deg=30.0,
+        polarization=polarization,
+        fourier_orders=12,
+        options=NeviereOptions(step_phase=0.005),
+    )
+    n_top, n_bottom, _ = prepare_layer_stack(aa, profile)
+    balance = propagating_energy_balance(
+        neviere.inc_top_reflected,
+        neviere.inc_top_transmitted,
+        wavelength=aa.wavelength,
+        period=aa.period,
+        beta0=aa.beta0,
+        n_top=n_top,
+        n_bottom=n_bottom,
+    )
+
+    assert balance["reflected"] > 0.0
+    assert balance["transmitted"] > 0.0
+    assert balance["total"] == pytest.approx(1.0, abs=1e-9)
+
+
+@pytest.mark.unit
+@pytest.mark.parametrize("polarization", ["s", "p"])
+@pytest.mark.parametrize("grazing_angle_deg", [30.0, 60.0])
+def test_neviere_reproduces_analytic_fresnel_in_the_flat_limit(
+    polarization: str,
+    grazing_angle_deg: float,
+) -> None:
+    """Verify a zero-depth grating returns the analytic single-interface reflectivity.
+
+    This pins the absolute normalization of the solver, independently of RCWA:
+    with no groove the structure is a plain vacuum/substrate interface, so the
+    zeroth order must equal the Fresnel reflectivity and every other order must
+    vanish.
+    """
+
+    energy_ev = 500.0
+    k0 = 2.0 * np.pi / (1239.8 / energy_ev)
+    kx = k0 * np.sin(np.deg2rad(90.0 - grazing_angle_deg))
+    kz_vacuum = np.sqrt(complex(k0**2 - kx**2))
+    kz_substrate = np.sqrt(complex((k0 * LOSSLESS_INDEX) ** 2 - kx**2))
+    if polarization == "s":
+        reflection = (kz_vacuum - kz_substrate) / (kz_vacuum + kz_substrate)
+    else:
+        substrate_admittance = kz_substrate / LOSSLESS_INDEX**2
+        reflection = (kz_vacuum - substrate_admittance) / (kz_vacuum + substrate_admittance)
+    expected_efficiency = float(abs(reflection) ** 2)
+
+    result = run_simulation(
+        grating=_sinusoidal_grating(depth_nm=0.0, material=LOSSLESS),
+        energy_ev=energy_ev,
+        grazing_angle_deg=grazing_angle_deg,
+        fourier_orders=6,
+        polarization=polarization,
+        solver="neviere",
+        validate_physical_results=False,
+    )
+
+    zeroth_index = int(np.argmin(np.abs(result.orders)))
+    other_efficiencies = np.delete(result.efficiency_all, zeroth_index)
+    assert result.efficiency_all[zeroth_index] == pytest.approx(expected_efficiency, rel=1e-9)
+    assert np.max(np.abs(other_efficiencies)) < 1e-20
+
+
+@pytest.mark.unit
+@pytest.mark.parametrize(
+    "roughness_kwargs",
+    [
+        pytest.param({"roughness_sigma_nm": 0.5}, id="solver-debye-waller"),
+        pytest.param(
+            {"roughness": grax.RoughnessSpec(kind="debye-waller", sigma_nm=0.5)},
+            id="grating-debye-waller",
+        ),
+        pytest.param(
+            {
+                "roughness": grax.RoughnessSpec(
+                    kind="random-interface",
+                    sigma_nm=0.3,
+                    num_supercells=2,
+                    num_realizations=2,
+                    seed=7,
+                )
+            },
+            id="random-interface-supercell",
+        ),
+    ],
+)
+def test_neviere_matches_rcwa_through_the_roughness_paths(
+    roughness_kwargs: dict[str, object],
+) -> None:
+    """Verify roughness reaches both solvers identically.
+
+    Roughness is applied around the solve rather than inside it, but the
+    supercell path also changes the period, the order grid and the realization
+    averaging, so it is worth pinning that the differential method threads
+    through all of it unchanged.
+    """
+
+    grating_kwargs = dict(roughness_kwargs)
+    solver_kwargs: dict[str, object] = {}
+    if "roughness_sigma_nm" in grating_kwargs:
+        solver_kwargs["roughness_sigma_nm"] = grating_kwargs.pop("roughness_sigma_nm")
+
+    common = dict(
+        grating=dataclasses.replace(_laminar_grating(), **grating_kwargs),
+        energy_ev=300.0,
+        grazing_angle_deg=4.0,
+        fourier_orders=6,
+        polarization="p",
+        validate_physical_results=False,
+        **solver_kwargs,
+    )
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore", UserWarning)
+        rcwa_result = run_simulation(**common, solver="rcwa")
+        neviere_result = run_simulation(**common, solver="neviere")
+
+    assert np.array_equal(rcwa_result.orders, neviere_result.orders)
+    assert np.allclose(
+        rcwa_result.efficiency_all,
+        neviere_result.efficiency_all,
+        atol=SOLVER_PARITY_ATOL,
+        rtol=SOLVER_PARITY_RTOL,
+    )
+    assert neviere_result.num_supercells == rcwa_result.num_supercells
+    assert neviere_result.num_realizations == rcwa_result.num_realizations
+
+
+@pytest.mark.unit
+def test_neviere_converges_to_rcwa_as_step_phase_shrinks() -> None:
+    """Verify the residual against RCWA is Runge-Kutta truncation error."""
+
+    grating = _laminar_grating()
+    parm = res0(-1)
+    textures, profile = grating.build_textures(300.0, n_inc=1.0 + 0.0j)
+    aa = res1(
+        1239.8 / 300.0,
+        grating.period_nm,
+        textures,
+        10,
+        np.sin(np.deg2rad(86.0)),
+        parm,
+        _fourier_backend="numba",
+    )
+    reference = np.real(res2(aa, profile, parm).inc_top_reflected.efficiency)
+
+    deviations = []
+    for step_phase in (0.4, 0.2, 0.1):
+        efficiency = np.real(
+            res2_dm(
+                aa,
+                profile,
+                parm,
+                options=NeviereOptions(step_phase=step_phase),
+            ).inc_top_reflected.efficiency
+        )
+        deviations.append(float(np.max(np.abs(efficiency - reference))))
+
+    assert deviations[0] > deviations[1] > deviations[2]
+    # Fourth-order accuracy: halving the step should cut the error by ~16.
+    assert deviations[1] < deviations[0] / 8.0
+    assert deviations[2] < deviations[1] / 8.0
+
+
+@pytest.mark.unit
+def test_continuous_sampling_is_independent_of_z_resolution() -> None:
+    """Verify continuous sampling ignores the staircase the RCWA path depends on.
+
+    The staircase solvers converge towards the continuous answer as
+    ``z_resolution_nm`` shrinks, while continuous sampling reads the true profile
+    and so returns the same efficiencies at every z resolution.
+    """
+
+    results = []
+    staircase_deviations = []
+    for z_resolution_nm in (1.0, 0.25):
+        grating = _sinusoidal_grating(depth_nm=10.0, z_resolution_nm=z_resolution_nm)
+        common = dict(
+            grating=grating,
+            energy_ev=300.0,
+            grazing_angle_deg=5.0,
+            fourier_orders=8,
+            polarization="p",
+            validate_physical_results=False,
+        )
+        continuous = run_simulation(
+            **common,
+            solver="neviere",
+            solver_options=NeviereOptions(z_sampling="continuous", sample_phase=0.05),
+        )
+        staircase = run_simulation(**common, solver="rcwa")
+        results.append(np.asarray(continuous.efficiency_all, dtype=float))
+        staircase_deviations.append(
+            float(np.max(np.abs(staircase.efficiency_all - continuous.efficiency_all)))
+        )
+
+    assert np.allclose(results[0], results[1], atol=1e-12)
+    # The staircase result moves towards the continuous one as z refines.
+    assert staircase_deviations[1] < staircase_deviations[0] / 2.0
+
+
+@pytest.mark.unit
+def test_continuous_sampling_matches_a_finely_sliced_staircase() -> None:
+    """Verify continuous sampling agrees with RCWA once the staircase is converged."""
+
+    energy_ev = 300.0
+    fine = run_simulation(
+        grating=_sinusoidal_grating(depth_nm=10.0, z_resolution_nm=0.01),
+        energy_ev=energy_ev,
+        grazing_angle_deg=5.0,
+        fourier_orders=8,
+        polarization="p",
+        solver="rcwa",
+        validate_physical_results=False,
+    )
+    continuous = run_simulation(
+        grating=_sinusoidal_grating(depth_nm=10.0, z_resolution_nm=1.0),
+        energy_ev=energy_ev,
+        grazing_angle_deg=5.0,
+        fourier_orders=8,
+        polarization="p",
+        solver="neviere",
+        solver_options=NeviereOptions(z_sampling="continuous", sample_phase=0.01),
+        validate_physical_results=False,
+    )
+
+    assert np.allclose(fine.efficiency_all, continuous.efficiency_all, atol=1e-4)
+
+
+@pytest.mark.unit
+def test_continuous_sampling_requires_an_epsilon_sampler() -> None:
+    """Verify res2_dm rejects continuous sampling without a permittivity sampler."""
+
+    grating = _laminar_grating()
+    parm = res0(1)
+    textures, profile = grating.build_textures(300.0, n_inc=1.0 + 0.0j)
+    aa = res1(1239.8 / 300.0, grating.period_nm, textures, 4, 0.99, parm,
+              _fourier_backend="numba")
+
+    with pytest.raises(ValueError, match="requires an epsilon_sampler"):
+        res2_dm(aa, profile, parm, options=NeviereOptions(z_sampling="continuous"))
+
+
+@pytest.mark.unit
+def test_epsilon_sampler_reads_the_profile_between_solver_rows() -> None:
+    """Verify the continuous sampler resolves depths the z grid never lands on."""
+
+    grating = _sinusoidal_grating(depth_nm=10.0, z_resolution_nm=1.0)
+    parm = res0(1)
+    textures, _ = grating.build_textures(300.0, n_inc=1.0 + 0.0j)
+    aa = res1(1239.8 / 300.0, grating.period_nm, textures, 6, 0.996, parm,
+              _fourier_backend="numba")
+    sampler = build_grating_epsilon_sampler(
+        grating,
+        photon_energy_ev=300.0,
+        period_nm=grating.period_nm,
+        orders=aa.orders,
+    )
+
+    # Two depths inside the groove region, half a solver row apart.
+    first = sampler(6.25)
+    second = sampler(6.75)
+
+    assert not np.allclose(first.epsilon_fourier, second.epsilon_fourier)
+
+
+@pytest.mark.unit
+def test_neviere_options_reject_invalid_settings() -> None:
+    """Verify option validation covers each numerical setting."""
+
+    with pytest.raises(ValueError, match="z_sampling"):
+        NeviereOptions(z_sampling="staircase")  # type: ignore[arg-type]
+    with pytest.raises(ValueError, match="step_phase"):
+        NeviereOptions(step_phase=0.0)
+    with pytest.raises(ValueError, match="block_phase"):
+        NeviereOptions(block_phase=-1.0)
+    with pytest.raises(ValueError, match="sample_phase"):
+        NeviereOptions(sample_phase=-1.0)
+    with pytest.raises(ValueError, match="max_step_nm"):
+        NeviereOptions(max_step_nm=0.0)
+    with pytest.raises(ValueError, match="max_steps_per_layer"):
+        NeviereOptions(max_steps_per_layer=0)
+    with pytest.raises(ValueError, match="energy_balance_tolerance"):
+        NeviereOptions(energy_balance_tolerance=0.0)
+
+
+@pytest.mark.unit
+def test_coerce_neviere_options_accepts_none_mapping_and_instance() -> None:
+    """Verify option coercion covers the shapes callers and case dicts provide."""
+
+    assert coerce_neviere_options(None) == NeviereOptions()
+    assert coerce_neviere_options({"step_phase": 0.01}).step_phase == pytest.approx(0.01)
+    instance = NeviereOptions(block_phase=1.0)
+    assert coerce_neviere_options(instance) is instance
+    with pytest.raises(TypeError, match="NeviereOptions"):
+        coerce_neviere_options(0.5)  # type: ignore[arg-type]
+
+
+@pytest.mark.unit
+def test_neviere_options_round_trip_through_to_dict() -> None:
+    """Verify options serialize to a JSON-compatible mapping and back."""
+
+    options = NeviereOptions(z_sampling="continuous", step_phase=0.01, max_step_nm=0.2)
+    restored = coerce_neviere_options(json.loads(json.dumps(options.to_dict())))
+
+    assert restored == options
+
+
+@pytest.mark.unit
+def test_energy_balance_tolerance_raises_on_a_violated_balance() -> None:
+    """Verify the internal sanity check fires when the balance exceeds its bound."""
+
+    grating = _sinusoidal_grating(depth_nm=10.0, material=LOSSLESS)
+    parm = res0(1)
+    textures, profile = grating.build_textures(500.0, n_inc=1.0 + 0.0j)
+    aa = res1(
+        1239.8 / 500.0,
+        grating.period_nm,
+        textures,
+        8,
+        np.sin(np.deg2rad(60.0)),
+        parm,
+        _fourier_backend="numba",
+    )
+
+    # A lossless structure sits at exactly 1.0, so any bound below that must fire.
+    with pytest.raises(ValueError, match="energy balance"):
+        res2_dm(aa, profile, parm, options=NeviereOptions(energy_balance_tolerance=0.5))
+
+    # The same solve passes under a physical bound.
+    res2_dm(aa, profile, parm, options=NeviereOptions(energy_balance_tolerance=1.05))
+
+
+@pytest.mark.unit
+def test_run_simulation_rejects_an_unknown_solver() -> None:
+    """Verify the solver name is validated before any work happens."""
+
+    with pytest.raises(ValueError, match="solver must be one of"):
+        run_simulation(
+            grating=_laminar_grating(),
+            energy_ev=300.0,
+            grazing_angle_deg=4.0,
+            fourier_orders=4,
+            solver="differential",  # type: ignore[arg-type]
+        )
+
+
+@pytest.mark.unit
+def test_batch_runner_records_and_overrides_the_solver(tmp_path: Path) -> None:
+    """Verify the runner default, per-case override, and checkpoint round-trip."""
+
+    grating = _laminar_grating()
+    cases = list(
+        fixed_angle_cases(
+            grating=grating,
+            energies_ev=[300.0, 400.0],
+            grazing_angle_deg=4.0,
+            polarization="p",
+        )
+    )
+    checkpoint_dir = tmp_path / "checkpoints"
+    runner = BatchSimulationRunner(
+        fourier_orders=6,
+        solver="neviere",
+        checkpoint_dir=checkpoint_dir,
+        on_error="fail_fast",
+    )
+    results = list(runner.run_cases(cases))
+
+    assert [result.solver for result in results] == ["neviere", "neviere"]
+
+    records = [
+        json.loads(line)
+        for line in (checkpoint_dir / "results.jsonl").read_text(encoding="utf-8").splitlines()
+        if line.strip()
+    ]
+    restored = [_case_result_from_record(record) for record in records]
+    assert [result.solver for result in restored] == ["neviere", "neviere"]
+
+    mixed = [dict(cases[0], solver="rcwa"), dict(cases[1], solver="neviere")]
+    mixed_runner = BatchSimulationRunner(fourier_orders=6, on_error="fail_fast")
+    assert [result.solver for result in mixed_runner.run_cases(mixed)] == ["rcwa", "neviere"]
+
+
+@pytest.mark.unit
+def test_batch_runner_rejects_an_unknown_solver() -> None:
+    """Verify the runner validates its default solver at construction time."""
+
+    with pytest.raises(ValueError, match="solver must be one of"):
+        BatchSimulationRunner(solver="dm")
+
+
+@pytest.mark.unit
+def test_rcwa_1d_alias_module_still_exposes_the_historical_names() -> None:
+    """Verify the compatibility shim covers every name the repo used to import."""
+
+    historical_names = [
+        "ArrayLike",
+        "BoundaryBlockCache",
+        "DiffractionResult",
+        "EigenCache",
+        "FourierBackend",
+        "Parameters",
+        "Res1Result",
+        "Res2Result",
+        "Texture1D",
+        "_angles_from_kx",
+        "_apply_debye_waller_roughness",
+        "_cascade_boundary_pair",
+        "_convolution_matrix",
+        "_debye_waller_roughness_factor",
+        "_kz_branch",
+        "_kz_branch_array",
+        "_layer_boundary_block",
+        "_modal_function_matrices",
+        "_modal_function_matrix",
+        "_piecewise_fourier_coefficients",
+        "_solve_te_stack",
+        "_solve_tm_stack",
+        "debye_waller_roughness_diagnostics",
+        "res0",
+        "res1",
+        "res2",
+        "safe_linalg_solve",
+    ]
+
+    missing = [name for name in historical_names if not hasattr(rcwa_1d, name)]
+    assert missing == []
+    assert rcwa_1d.res2 is res2
+    assert rcwa_1d.res2_dm is res2_dm
+    assert grax.NeviereOptions is NeviereOptions
+
+
+@pytest.mark.unit
+def test_multilayer_theta_search_honours_the_requested_solver() -> None:
+    """Verify the theta-search workflow does not silently fall back to RCWA.
+
+    The batch runner builds a separate payload for this workflow. That payload
+    carried ``backend`` but not ``solver``, so a runner configured for the
+    differential method quietly computed with RCWA instead: no error, no warning,
+    and a result that correctly reported the solver that actually ran rather than
+    the one that was asked for.
+    """
+
+    cases = list(
+        multilayer_theta_search_cases(
+            grating=_multilayer_grating(),
+            energies_ev=[500.0],
+            diffraction_order=2,
+            rough_scan_half_width_deg=0.4,
+            rough_scan_points=5,
+            rough_fourier_orders=2,
+            rough_x_resolution_nm=4.0,
+            rough_z_resolution_nm=2.0,
+            fine_scan_half_width_deg=0.1,
+            fine_scan_points=5,
+            fine_fourier_orders=2,
+            fine_x_resolution_nm=4.0,
+            fine_z_resolution_nm=2.0,
+            final_fourier_orders=3,
+            final_x_resolution_nm=4.0,
+            final_z_resolution_nm=2.0,
+        )
+    )
+    runner = BatchSimulationRunner(
+        fourier_orders=3,
+        solver="neviere",
+        on_error="fail_fast",
+    )
+
+    results = list(runner.run_cases(cases))
+
+    assert [result.solver for result in results] == ["neviere"]
+
+
+@pytest.mark.unit
+def test_multilayer_theta_search_agrees_across_solvers() -> None:
+    """Verify both solvers select the same angle and efficiency for a theta search."""
+
+    search_kwargs = dict(
+        grating=_multilayer_grating(),
+        energy_ev=500.0,
+        diffraction_order=2,
+        initial_grazing_angle_deg=14.176,
+        rough_scan_half_width_deg=0.4,
+        rough_scan_points=5,
+        rough_fourier_orders=2,
+        rough_x_resolution_nm=4.0,
+        rough_z_resolution_nm=2.0,
+        fine_scan_half_width_deg=0.1,
+        fine_scan_points=5,
+        fine_fourier_orders=2,
+        fine_x_resolution_nm=4.0,
+        fine_z_resolution_nm=2.0,
+        final_fourier_orders=3,
+        final_x_resolution_nm=4.0,
+        final_z_resolution_nm=2.0,
+        validate_physical_results=False,
+    )
+    rcwa_result = run_multilayer_theta_search(**search_kwargs, solver="rcwa")
+    neviere_result = run_multilayer_theta_search(**search_kwargs, solver="neviere")
+
+    assert neviere_result.solver == "neviere"
+    assert rcwa_result.solver == "rcwa"
+    assert neviere_result.grazing_angle_deg == pytest.approx(
+        rcwa_result.grazing_angle_deg, abs=1e-9
+    )
+    assert neviere_result.selected_efficiency == pytest.approx(
+        rcwa_result.selected_efficiency,
+        abs=SOLVER_PARITY_ATOL,
+        rel=SOLVER_PARITY_RTOL,
+    )
+
+
+@pytest.mark.unit
+def test_solver_options_round_trip_through_a_checkpoint(tmp_path: Path) -> None:
+    """Verify a checkpointed differential-method run records its integration settings.
+
+    The solver name alone does not pin the result: the same "neviere" label
+    covers every ``step_phase`` and both sampling modes. Recording the options
+    makes a resumed or archived run reproducible.
+    """
+
+    options = NeviereOptions(step_phase=0.01, block_phase=1.5)
+    checkpoint_dir = tmp_path / "checkpoints"
+    runner = BatchSimulationRunner(
+        fourier_orders=5,
+        solver="neviere",
+        solver_options=options,
+        checkpoint_dir=checkpoint_dir,
+        on_error="fail_fast",
+    )
+    cases = list(
+        fixed_angle_cases(
+            grating=_laminar_grating(),
+            energies_ev=[300.0],
+            grazing_angle_deg=4.0,
+        )
+    )
+
+    results = list(runner.run_cases(cases))
+    assert results[0].solver_options == options.to_dict()
+
+    records = [
+        json.loads(line)
+        for line in (checkpoint_dir / "results.jsonl").read_text(encoding="utf-8").splitlines()
+        if line.strip()
+    ]
+    restored = _case_result_from_record(records[0])
+
+    assert restored.solver_options == options.to_dict()
+    assert NeviereOptions(**restored.solver_options) == options
+
+
+@pytest.mark.unit
+def test_rcwa_results_record_no_solver_options() -> None:
+    """Verify the RCWA path leaves solver_options unset rather than inventing one."""
+
+    result = run_simulation(
+        grating=_laminar_grating(),
+        energy_ev=300.0,
+        grazing_angle_deg=4.0,
+        fourier_orders=5,
+    )
+
+    assert result.solver == "rcwa"
+    assert result.solver_options is None
+
+
+@pytest.mark.unit
+def test_grating_simulation_replaces_the_rcwa_specific_name() -> None:
+    """Verify the renamed wrapper is the only spelling and drives both solvers.
+
+    ``RCWASimulation`` described only one of the two solvers it can now run.
+    This is a deliberate breaking rename with no alias.
+    """
+
+    assert not hasattr(grax.simulation, "RCWASimulation")
+    assert "RCWASimulation" not in dir(grax.simulation)
+
+    grating = _laminar_grating()
+    rcwa = grax.simulation.GratingSimulation(
+        grating=grating,
+        fourier_orders=5,
+        polarization="p",
+        validate_physical_results=False,
+    ).run_single(300.0)
+    neviere = grax.simulation.GratingSimulation(
+        grating=grating,
+        fourier_orders=5,
+        polarization="p",
+        solver="neviere",
+        validate_physical_results=False,
+    ).run_single(300.0)
+
+    assert np.allclose(
+        rcwa["efficiency_all"],
+        neviere["efficiency_all"],
+        atol=SOLVER_PARITY_ATOL,
+        rtol=SOLVER_PARITY_RTOL,
+    )
+
+
+# --------------------------------------------------------------------------
+# Coverage for the entry points the examples use.
+#
+# Each of these is exercised by an example script, so each must be shown to
+# work with either solver. Without this section a reader could swap --solver on
+# an example and hit an untested path.
+# --------------------------------------------------------------------------
+
+
+def _selected_efficiencies(results) -> np.ndarray:
+    """Return the selected-order efficiency of every successful case."""
+
+    return np.asarray(
+        [result.selected_efficiency for result in results if result.status == "ok"],
+        dtype=float,
+    )
+
+
+def _run_cases_with(solver: str, cases, **runner_kwargs):
+    """Run one case iterable through the batch runner with one solver."""
+
+    runner = BatchSimulationRunner(
+        fourier_orders=6,
+        on_error="fail_fast",
+        solver=solver,
+        **runner_kwargs,
+    )
+    return list(runner.run_cases(cases))
+
+
+@pytest.mark.unit
+def test_monochromator_cases_agree_across_solvers() -> None:
+    """Verify the monochromator case builder works with either solver.
+
+    ``monochromator_cases`` is the case builder the examples use most, and its
+    grazing angle is solved per energy from the cff condition rather than given,
+    so it is worth confirming both solvers see the same geometry.
+    """
+
+    energies_ev = [200.0, 400.0, 600.0]
+
+    def build():
+        return monochromator_cases(
+            grating=_laminar_grating(),
+            energies_ev=energies_ev,
+            diffraction_order=1,
+            cff=2.25,
+            polarization="p",
+        )
+
+    rcwa_results = _run_cases_with("rcwa", build())
+    neviere_results = _run_cases_with("neviere", build())
+
+    assert [result.grazing_angle_deg for result in rcwa_results] == [
+        result.grazing_angle_deg for result in neviere_results
+    ]
+    assert np.allclose(
+        _selected_efficiencies(rcwa_results),
+        _selected_efficiencies(neviere_results),
+        atol=SOLVER_PARITY_ATOL,
+        rtol=SOLVER_PARITY_RTOL,
+    )
+    assert {result.solver for result in neviere_results} == {"neviere"}
+
+
+@pytest.mark.unit
+def test_energy_angle_cases_agree_across_solvers() -> None:
+    """Verify the explicit energy-angle case builder works with either solver."""
+
+    pairs = [(300.0, 4.0), (500.0, 3.0), (800.0, 2.0)]
+
+    def build():
+        return energy_angle_cases(
+            grating=_laminar_grating(),
+            energy_angle_pairs=pairs,
+            polarization="p",
+        )
+
+    rcwa_results = _run_cases_with("rcwa", build())
+    neviere_results = _run_cases_with("neviere", build())
+
+    assert np.allclose(
+        _selected_efficiencies(rcwa_results),
+        _selected_efficiencies(neviere_results),
+        atol=SOLVER_PARITY_ATOL,
+        rtol=SOLVER_PARITY_RTOL,
+    )
+
+
+@pytest.mark.unit
+def test_parameter_study_agrees_across_solvers() -> None:
+    """Verify the convergence parameter study runs on either solver.
+
+    ``run_parameter_study`` drives ``GratingSimulation`` rather than the batch
+    runner, so it is a separate path to the solver from every other entry point.
+    """
+
+    common = dict(
+        grating=_laminar_grating(),
+        energies_ev=[300.0],
+        grazing_angle_deg=4.0,
+        polarization="p",
+        fourier_orders_values=[4, 6],
+        x_resolution_values=[8.0, 4.0],
+        z_resolution_values=[2.0, 1.0],
+        save_csv=False,
+        show_progress=False,
+    )
+    rcwa_study = grax.run_parameter_study(**common, solver="rcwa")
+    neviere_study = grax.run_parameter_study(**common, solver="neviere")
+
+    for energy_result_rcwa, energy_result_neviere in zip(
+        rcwa_study.results, neviere_study.results
+    ):
+        for parameter in ("fourier_orders", "x_resolution_nm", "z_resolution_nm"):
+            assert np.allclose(
+                energy_result_rcwa.sweeps[parameter].efficiencies,
+                energy_result_neviere.sweeps[parameter].efficiencies,
+                atol=SOLVER_PARITY_ATOL,
+                rtol=SOLVER_PARITY_RTOL,
+            )
+
+
+@pytest.mark.unit
+def test_theta_search_sweep_agrees_across_solvers(tmp_path: Path) -> None:
+    """Verify the multi-energy theta-search sweep runs on either solver.
+
+    The sweep has its own runner-settings construction separate from
+    ``BatchSimulationRunner``; that is where ``solver`` was previously dropped.
+    """
+
+    common = dict(
+        grating=_multilayer_grating(),
+        energies_ev=[500.0],
+        diffraction_order=2,
+        rough_scan_half_width_deg=0.4,
+        rough_scan_points=5,
+        rough_fourier_orders=2,
+        rough_x_resolution_nm=4.0,
+        rough_z_resolution_nm=2.0,
+        fine_scan_half_width_deg=0.1,
+        fine_scan_points=5,
+        fine_fourier_orders=2,
+        fine_x_resolution_nm=4.0,
+        fine_z_resolution_nm=2.0,
+        final_fourier_orders=3,
+        final_x_resolution_nm=4.0,
+        final_z_resolution_nm=2.0,
+        show_progress=False,
+        save_profile_plot=False,
+        save_stack_plot=False,
+    )
+    rcwa_sweep = grax.run_multilayer_theta_search_sweep(
+        **common, output_dir=tmp_path / "rcwa", solver="rcwa"
+    )
+    neviere_sweep = grax.run_multilayer_theta_search_sweep(
+        **common, output_dir=tmp_path / "neviere", solver="neviere"
+    )
+
+    rcwa_case = rcwa_sweep.batch_result.cases[0]
+    neviere_case = neviere_sweep.batch_result.cases[0]
+    assert neviere_case.solver == "neviere"
+    assert rcwa_case.solver == "rcwa"
+    assert neviere_case.grazing_angle_deg == pytest.approx(
+        rcwa_case.grazing_angle_deg, abs=1e-9
+    )
+    assert neviere_case.selected_efficiency == pytest.approx(
+        rcwa_case.selected_efficiency,
+        abs=SOLVER_PARITY_ATOL,
+        rel=SOLVER_PARITY_RTOL,
+    )
+    # The sweep builds its own CaseExecutionResult rather than reusing the
+    # runner's, and used to copy only the diagnostics across. solver and
+    # solver_options fell back to their dataclass defaults, so a neviere sweep
+    # reported itself as an rcwa one while computing the right answer -- the two
+    # results above differ by ~5e-14, so the solve was correct and only the
+    # provenance was wrong.
+    assert neviere_case.solver_options is not None
+    assert rcwa_case.solver_options is None
+    # This workflow does not expose polarization, so it is always s.
+    assert neviere_case.polarization == "s"
+
+
+@pytest.mark.unit
+def test_custom_stack_agrees_across_solvers() -> None:
+    """Verify a hand-assembled layer stack works with either solver.
+
+    ``assemble_custom_stack`` produces a different stack class from
+    ``MultilayerStack``, and therefore a different texture-building path.
+    """
+
+    layers_bottom_up = [
+        grax.LayerSpec(material=PT, thickness_nm=3.0),
+        grax.LayerSpec(material=CR, thickness_nm=4.0),
+        grax.LayerSpec(material=C, thickness_nm=5.0),
+    ]
+    stack = grax.assemble_custom_stack(
+        substrate_material=SI,
+        layers_bottom_up=layers_bottom_up,
+        top_cap_material=C,
+        top_cap_thickness_nm=1.0,
+    )
+    grating = BlazedGrating(
+        period_lpermm=1200,
+        blaze_angle_deg=1.2,
+        anti_blaze_angle_deg=4.0,
+        coating_stack=stack,
+        x_resolution_nm=4.0,
+        z_resolution_nm=1.0,
+    )
+
+    _assert_solvers_agree(
+        grating,
+        energy_ev=400.0,
+        grazing_angle_deg=3.0,
+        polarization="p",
+        fourier_orders=6,
+    )
+
+
+@pytest.mark.unit
+def test_afm_grating_agrees_across_solvers() -> None:
+    """Verify a grating built from AFM data works with either solver.
+
+    ``AFMGrating`` subclasses ``ProfileGrating``, so this covers the
+    construction path rather than a new solver path, but the examples build
+    gratings this way and the swap has to hold for them too.
+    """
+
+    period_nm = 1e6 / 600
+    x_points_nm = np.linspace(0.0, period_nm, 65)
+    z_points_nm = 8.0 * (x_points_nm / period_nm)
+    grating = grax.AFMGrating(
+        period_lpermm=600,
+        x_points_nm=x_points_nm,
+        z_points_nm=z_points_nm,
+        substrate_material=SI,
+        layer_material=AU,
+        layer_thickness_nm=20.0,
+        x_resolution_nm=4.0,
+        z_resolution_nm=1.0,
+    )
+
+    _assert_solvers_agree(
+        grating,
+        energy_ev=400.0,
+        grazing_angle_deg=3.0,
+        polarization="p",
+        fourier_orders=6,
+    )
+
+
+@pytest.mark.unit
+def test_output_helpers_accept_either_solver_result(tmp_path: Path) -> None:
+    """Verify the export and plotting helpers work on either solver's results.
+
+    These are solver-agnostic by design; the check is that a differential-method
+    result carries everything they need, since every example ends by calling them.
+    """
+
+    cases = list(
+        fixed_angle_cases(
+            grating=_laminar_grating(),
+            energies_ev=[300.0, 400.0],
+            grazing_angle_deg=4.0,
+            polarization="p",
+        )
+    )
+    for solver in ("rcwa", "neviere"):
+        results = _run_cases_with(solver, list(cases))
+
+        csv_path = tmp_path / f"all_orders_{solver}.csv"
+        grax.write_all_orders_csv(results, csv_path)
+        assert csv_path.read_text(encoding="utf-8").count("\n") > 2
+
+        plot_path = tmp_path / f"orders_{solver}.png"
+        grax.plot_order_subset(results, plot_path, diffraction_orders=[1, 2], title=solver)
+        assert plot_path.exists()
+
+        efficiency = grax.efficiency_for_order(
+            results[0].orders, results[0].efficiency_all, diffraction_order=1
+        )
+        assert np.isfinite(efficiency)
diff --git a/tests/unit/test_parameter_sweep.py b/tests/unit/test_parameter_sweep.py
index 50d027d..9cff945 100644
--- a/tests/unit/test_parameter_sweep.py
+++ b/tests/unit/test_parameter_sweep.py
@@ -14,7 +14,7 @@
     plot_parameter_study,
     run_parameter_study,
 )
-from grax.simulation import RCWASimulation
+from grax.simulation import GratingSimulation
 
 
 def test_run_parameter_study_returns_expected_shapes(
@@ -38,7 +38,7 @@ def fake_run_single(self, photon_energy_ev: float) -> dict[str, object]:
             "diffraction_angle_all": np.asarray([1.0, 2.0, 3.0], dtype=float),
         }
 
-    monkeypatch.setattr(RCWASimulation, "run_single", fake_run_single)
+    monkeypatch.setattr(GratingSimulation, "run_single", fake_run_single)
 
     grating = BlazedGrating(
         period_lpermm=600,
@@ -93,7 +93,7 @@ def test_run_parameter_study_preserves_error_messages_in_csv(
     def fake_run_single(self, photon_energy_ev: float) -> dict[str, object]:
         raise ValueError(f"failed at {photon_energy_ev:.1f} eV")
 
-    monkeypatch.setattr(RCWASimulation, "run_single", fake_run_single)
+    monkeypatch.setattr(GratingSimulation, "run_single", fake_run_single)
 
     result = run_parameter_study(
         grating=BlazedGrating(period_lpermm=600, blaze_angle_deg=0.75),
@@ -131,7 +131,7 @@ def fake_run_single(self, photon_energy_ev: float) -> dict[str, object]:
             "diffraction_angle_all": np.asarray([1.0, 2.0, 3.0], dtype=float),
         }
 
-    monkeypatch.setattr(RCWASimulation, "run_single", fake_run_single)
+    monkeypatch.setattr(GratingSimulation, "run_single", fake_run_single)
 
     grating = BlazedGrating(period_lpermm=600, blaze_angle_deg=0.75)
     result = run_parameter_study(
@@ -224,7 +224,7 @@ def fake_run_single(self, photon_energy_ev: float) -> dict[str, object]:
             "diffraction_angle_all": np.asarray([1.0, 2.0, 3.0], dtype=float),
         }
 
-    monkeypatch.setattr(RCWASimulation, "run_single", fake_run_single)
+    monkeypatch.setattr(GratingSimulation, "run_single", fake_run_single)
 
     grating = BlazedGrating(
         period_lpermm=600,
diff --git a/tests/unit/test_polarization_aliases.py b/tests/unit/test_polarization_aliases.py
new file mode 100644
index 0000000..ec5d5ee
--- /dev/null
+++ b/tests/unit/test_polarization_aliases.py
@@ -0,0 +1,323 @@
+"""Tests for the TE/TM polarization aliases and theta-search polarization."""
+
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+import numpy as np
+import pytest
+
+import grax
+from grax.simulation import (
+    BatchSimulationRunner,
+    GratingSimulation,
+    fixed_angle_cases,
+    monochromator_cases,
+    multilayer_theta_search_cases,
+    run_multilayer_theta_search,
+    run_simulation,
+)
+from grax.simulation.core import POLARIZATION_ALIASES, normalize_polarization
+from grax.simulation.serialization import _case_result_from_record
+from tests.simulation_helpers import C, CR, PT, SI
+
+
+def _grating() -> grax.LaminarGrating:
+    """Return a coarse coated laminar grating."""
+
+    return grax.LaminarGrating(
+        period_lpermm=400,
+        width_to_period_ratio=0.67,
+        depth_nm=14.9,
+        left_wall_angle_deg=15.0,
+        right_wall_angle_deg=15.0,
+        substrate_material=SI,
+        layer_material=PT,
+        layer_thickness_nm=28.77,
+        x_resolution_nm=4.0,
+        z_resolution_nm=1.0,
+    )
+
+
+def _multilayer_grating() -> grax.BlazedGrating:
+    """Return a coarse blazed grating on a Cr/C multilayer stack."""
+
+    return grax.BlazedGrating(
+        period_lpermm=2400,
+        blaze_angle_deg=1.37,
+        anti_blaze_angle_deg=3.25,
+        coating_stack=grax.MultilayerStack(
+            substrate_material=SI,
+            material_a=CR,
+            material_b=C,
+            d_period_nm=4.8,
+            gamma=0.4,
+            n_bilayers=8,
+            top_material=C,
+        ),
+        x_resolution_nm=2.0,
+        z_resolution_nm=0.5,
+    )
+
+
+_THETA_SEARCH_KWARGS = dict(
+    diffraction_order=2,
+    initial_grazing_angle_deg=14.176,
+    rough_scan_half_width_deg=0.4,
+    rough_scan_points=5,
+    rough_fourier_orders=2,
+    rough_x_resolution_nm=4.0,
+    rough_z_resolution_nm=2.0,
+    fine_scan_half_width_deg=0.1,
+    fine_scan_points=5,
+    fine_fourier_orders=2,
+    fine_x_resolution_nm=4.0,
+    fine_z_resolution_nm=2.0,
+    final_fourier_orders=3,
+    final_x_resolution_nm=4.0,
+    final_z_resolution_nm=2.0,
+    validate_physical_results=False,
+)
+
+
+@pytest.mark.unit
+@pytest.mark.parametrize(
+    ("spelling", "canonical"),
+    [("s", "s"), ("S", "s"), ("te", "s"), ("TE", "s"), ("  Te  ", "s"),
+     ("p", "p"), ("P", "p"), ("tm", "p"), ("TM", "p"), (" tM ", "p")],
+)
+def test_normalize_polarization_maps_every_accepted_spelling(
+    spelling: str, canonical: str
+) -> None:
+    """Verify each accepted spelling canonicalizes, ignoring case and whitespace."""
+
+    assert normalize_polarization(spelling) == canonical
+
+
+@pytest.mark.unit
+@pytest.mark.parametrize("value", ["", "x", "tem", "s-pol", "1", "transverse electric"])
+def test_normalize_polarization_rejects_anything_else(value: str) -> None:
+    """Verify unknown spellings raise rather than silently picking a default."""
+
+    with pytest.raises(ValueError, match="polarization must be one of"):
+        normalize_polarization(value)
+
+
+@pytest.mark.unit
+def test_polarization_aliases_cover_both_states_only() -> None:
+    """Verify the alias table stays deliberately small."""
+
+    assert set(POLARIZATION_ALIASES.values()) == {"s", "p"}
+    assert set(POLARIZATION_ALIASES) == {"s", "te", "p", "tm"}
+
+
+@pytest.mark.unit
+@pytest.mark.parametrize(("alias", "canonical"), [("TE", "s"), ("TM", "p")])
+def test_run_simulation_alias_is_bit_identical_to_canonical(
+    alias: str, canonical: str
+) -> None:
+    """Verify an alias is a pure rename, not a different calculation.
+
+    Bit-identical rather than close: the alias resolves before any physics
+    happens, so anything other than an exact match would mean the two spellings
+    took different paths.
+    """
+
+    common = dict(
+        grating=_grating(),
+        energy_ev=300.0,
+        grazing_angle_deg=4.0,
+        fourier_orders=8,
+        validate_physical_results=False,
+    )
+    alias_result = run_simulation(**common, polarization=alias)
+    canonical_result = run_simulation(**common, polarization=canonical)
+
+    assert alias_result.polarization == canonical
+    assert np.array_equal(alias_result.efficiency_all, canonical_result.efficiency_all)
+    assert alias_result.selected_efficiency == canonical_result.selected_efficiency
+
+
+@pytest.mark.unit
+def test_s_and_p_still_differ() -> None:
+    """Guard the alias test above: s and p must not be accidentally equal."""
+
+    common = dict(
+        grating=_grating(),
+        energy_ev=300.0,
+        grazing_angle_deg=4.0,
+        fourier_orders=8,
+        validate_physical_results=False,
+    )
+    assert run_simulation(**common, polarization="s").selected_efficiency != (
+        run_simulation(**common, polarization="p").selected_efficiency
+    )
+
+
+@pytest.mark.unit
+def test_grating_simulation_accepts_an_alias() -> None:
+    """Verify the compatibility wrapper canonicalizes too."""
+
+    simulation = GratingSimulation(
+        grating=_grating(),
+        fourier_orders=6,
+        polarization="TM",
+        validate_physical_results=False,
+    )
+    assert simulation.run_single(300.0)["efficiency"] == pytest.approx(
+        GratingSimulation(
+            grating=_grating(),
+            fourier_orders=6,
+            polarization="p",
+            validate_physical_results=False,
+        ).run_single(300.0)["efficiency"]
+    )
+
+
+@pytest.mark.unit
+def test_batch_runner_canonicalizes_runner_and_case_polarization(tmp_path: Path) -> None:
+    """Verify aliases work as a runner setting and as a per-case override."""
+
+    runner = BatchSimulationRunner(
+        fourier_orders=6,
+        polarization="TM",
+        checkpoint_dir=tmp_path / "checkpoints",
+        on_error="fail_fast",
+    )
+    assert runner.polarization == "p"
+
+    cases = list(
+        fixed_angle_cases(
+            grating=_grating(),
+            energies_ev=[300.0],
+            grazing_angle_deg=4.0,
+            polarization="TE",
+        )
+    )
+    results = list(runner.run_cases(cases))
+
+    assert results[0].polarization == "s"
+
+    records = [
+        json.loads(line)
+        for line in (tmp_path / "checkpoints" / "results.jsonl").read_text(
+            encoding="utf-8"
+        ).splitlines()
+        if line.strip()
+    ]
+    assert _case_result_from_record(records[0]).polarization == "s"
+
+
+@pytest.mark.unit
+def test_case_builders_accept_aliases() -> None:
+    """Verify the case builders pass an alias through for the runner to resolve."""
+
+    monochromator = list(
+        monochromator_cases(
+            grating=_grating(), energies_ev=[300.0], cff=2.25, polarization="TM"
+        )
+    )
+    theta_search = list(
+        multilayer_theta_search_cases(
+            grating=_multilayer_grating(), energies_ev=[500.0], polarization="TE"
+        )
+    )
+
+    assert monochromator[0]["polarization"] == "TM"
+    assert theta_search[0]["polarization"] == "TE"
+
+
+@pytest.mark.unit
+def test_parameter_study_rejects_a_bad_polarization_at_the_entry_point() -> None:
+    """Verify the parameter study validates rather than failing three frames down."""
+
+    with pytest.raises(ValueError, match="polarization must be one of"):
+        grax.run_parameter_study(
+            grating=_grating(),
+            energies_ev=[300.0],
+            grazing_angle_deg=4.0,
+            polarization="tem",
+            save_csv=False,
+            show_progress=False,
+        )
+
+
+@pytest.mark.unit
+@pytest.mark.parametrize("solver", ["rcwa", "neviere"])
+def test_theta_search_polarization_reaches_the_solver(solver: str) -> None:
+    """Verify the theta search actually solves in the requested polarization.
+
+    This workflow had no polarization argument at all, so every search ran the
+    ``run_simulation`` default. Asserting only that ``p`` runs would pass even if
+    the value were stored and ignored; the check that matters is that ``p``
+    selects a different angle and efficiency from ``s``.
+    """
+
+    s_result = run_multilayer_theta_search(
+        grating=_multilayer_grating(), energy_ev=500.0, solver=solver,
+        polarization="s", **_THETA_SEARCH_KWARGS,
+    )
+    p_result = run_multilayer_theta_search(
+        grating=_multilayer_grating(), energy_ev=500.0, solver=solver,
+        polarization="p", **_THETA_SEARCH_KWARGS,
+    )
+
+    assert s_result.polarization == "s"
+    assert p_result.polarization == "p"
+    assert p_result.selected_efficiency != s_result.selected_efficiency
+    assert p_result.grazing_angle_deg != s_result.grazing_angle_deg
+
+
+@pytest.mark.unit
+def test_theta_search_alias_is_bit_identical_to_canonical() -> None:
+    """Verify TM reaches the theta search as exactly p."""
+
+    alias = run_multilayer_theta_search(
+        grating=_multilayer_grating(), energy_ev=500.0,
+        polarization="TM", **_THETA_SEARCH_KWARGS,
+    )
+    canonical = run_multilayer_theta_search(
+        grating=_multilayer_grating(), energy_ev=500.0,
+        polarization="p", **_THETA_SEARCH_KWARGS,
+    )
+
+    assert alias.polarization == "p"
+    assert alias.grazing_angle_deg == canonical.grazing_angle_deg
+    assert alias.selected_efficiency == canonical.selected_efficiency
+
+
+@pytest.mark.unit
+def test_theta_search_batch_workflow_honours_polarization() -> None:
+    """Verify the batch payload for this workflow carries polarization.
+
+    That payload is built separately from the plain-case one and previously had
+    no polarization key at all, which is the same shape of gap that let ``solver``
+    go missing from it.
+    """
+
+    cases = list(
+        multilayer_theta_search_cases(
+            grating=_multilayer_grating(),
+            energies_ev=[500.0],
+            diffraction_order=2,
+            rough_scan_half_width_deg=0.4,
+            rough_scan_points=5,
+            rough_fourier_orders=2,
+            rough_x_resolution_nm=4.0,
+            rough_z_resolution_nm=2.0,
+            fine_scan_half_width_deg=0.1,
+            fine_scan_points=5,
+            fine_fourier_orders=2,
+            fine_x_resolution_nm=4.0,
+            fine_z_resolution_nm=2.0,
+            final_fourier_orders=3,
+            final_x_resolution_nm=4.0,
+            final_z_resolution_nm=2.0,
+            polarization="TM",
+        )
+    )
+    runner = BatchSimulationRunner(fourier_orders=3, on_error="fail_fast")
+    results = list(runner.run_cases(cases))
+
+    assert results[0].polarization == "p"
diff --git a/tests/unit/test_profiling.py b/tests/unit/test_profiling.py
index 8b73246..1bba556 100644
--- a/tests/unit/test_profiling.py
+++ b/tests/unit/test_profiling.py
@@ -15,6 +15,7 @@
 from grax.gratings import BaseGrating, LaminarGrating
 from grax import rcwa_1d
 from grax.rcwa_1d import res0, res1
+from grax.solvers import common as solvers_common
 from grax.simulation import core as simulation_core_module
 from grax.simulation.batch import BatchSimulationRunner
 from grax.simulation import run_simulation
@@ -321,7 +322,7 @@ def __exit__(self, exc_type: object, exc_value: object, traceback: object) -> No
             fourier_orders=15,
         )
 
-    assert "Running simulation at 500.00 eV" in caplog.text
+    assert "Running rcwa simulation at 500.00 eV" in caplog.text
     assert "peak_ram=" not in caplog.text
 
 
@@ -754,9 +755,12 @@ def test_blazed_multilayer_optimized_cascade_matches_legacy_cascade() -> None:
         _memory_mode="low_memory",
     )
 
-    original_cascade = rcwa_1d._cascade_boundary_pair
+    # Patch the defining module, not the ``grax.rcwa_1d`` alias: the solvers call
+    # the name they resolve in ``grax.solvers.common``, so rebinding the alias
+    # would silently leave the optimized cascade in place.
+    original_cascade = solvers_common._cascade_boundary_pair
     try:
-        rcwa_1d._cascade_boundary_pair = _legacy_cascade_boundary_pair
+        solvers_common._cascade_boundary_pair = _legacy_cascade_boundary_pair
         legacy = run_simulation(
             grating=grating,
             energy_ev=500.0,
@@ -766,7 +770,7 @@ def test_blazed_multilayer_optimized_cascade_matches_legacy_cascade() -> None:
             _memory_mode="low_memory",
         )
     finally:
-        rcwa_1d._cascade_boundary_pair = original_cascade
+        solvers_common._cascade_boundary_pair = original_cascade
 
     assert optimized.selected_efficiency == pytest.approx(
         legacy.selected_efficiency,
diff --git a/tests/unit/test_reticolopy_opt.py b/tests/unit/test_reticolopy_opt.py
index 3384838..08ae3ad 100644
--- a/tests/unit/test_reticolopy_opt.py
+++ b/tests/unit/test_reticolopy_opt.py
@@ -1,5 +1,7 @@
 from __future__ import annotations
 
+import dataclasses
+
 import json
 import runpy
 from pathlib import Path
@@ -554,3 +556,73 @@ def test_example_configs_split_optimizer_and_simulation_backends() -> None:
     assert laminar_config["simulation_backend"] == "numba"
     assert "optimizer_max_workers" in laminar_config
     assert blazed_config["simulation_backend"] == laminar_config["simulation_backend"]
+
+
+def test_measurement_fit_config_accepts_and_validates_the_solver(tmp_path: Path) -> None:
+    """Verify the optimizer can be pointed at either solver."""
+
+    default_config = _build_measurement_fit_config(tmp_path)
+    assert default_config.solver == "rcwa"
+    assert default_config.solver_options is None
+
+    neviere_config = dataclasses.replace(
+        default_config,
+        solver="neviere",
+        solver_options={"step_phase": 0.01},
+    )
+    assert neviere_config.solver == "neviere"
+    assert neviere_config.solver_options == {"step_phase": 0.01}
+
+    with pytest.raises(ValueError, match="solver must be one of"):
+        dataclasses.replace(default_config, solver="differential")
+
+
+def test_measurement_fit_trial_runner_uses_the_configured_solver(
+    tmp_path: Path,
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    """Verify a trial evaluation builds its batch runner with the config's solver.
+
+    The optimizer reads the solver off the config rather than taking it as an
+    argument, the same way it reads ``diffraction_order`` and ``fourier_orders``.
+    This pins that it actually reaches the runner.
+    """
+
+    captured: dict[str, object] = {}
+
+    class _RecordingRunner:
+        resolved_max_workers = 1
+
+        def __init__(self, **kwargs: object) -> None:
+            captured.update(kwargs)
+
+        def run_cases(self, cases):
+            raise RuntimeError("stop after construction")
+
+    monkeypatch.setattr(objective_module, "BatchSimulationRunner", _RecordingRunner)
+
+    config = dataclasses.replace(
+        _build_measurement_fit_config(tmp_path),
+        solver="neviere",
+        solver_options={"step_phase": 0.01},
+    )
+    measurement = load_measurement_data(config.measurement_path)
+
+    with pytest.raises(RuntimeError, match="stop after construction"):
+        objective_module.simulate_efficiency_curve_with_metadata(
+            config,
+            {"period_lpermm": 400.0},
+            measurement,
+            backend="numba",
+            build_grating_fn=lambda parameters: _FakeGrating(),
+            resolve_solver_parameters_fn=lambda parameters: {"roughness_sigma_nm": None},
+        )
+
+    assert captured["solver"] == "neviere"
+    assert captured["solver_options"] == {"step_phase": 0.01}
+
+
+class _FakeGrating:
+    """Minimal grating stand-in for the runner-construction test."""
+
+    period_lpermm = 400.0
diff --git a/tests/unit/test_simulation_core.py b/tests/unit/test_simulation_core.py
index f995a99..dbc2467 100644
--- a/tests/unit/test_simulation_core.py
+++ b/tests/unit/test_simulation_core.py
@@ -25,7 +25,7 @@
     BatchSimulationRunner,
     CaseExecutionResult,
     MultilayerThetaSearchSweepResult,
-    RCWASimulation,
+    GratingSimulation,
     SingleSimulationResult,
     efficiency_for_order,
     energy_angle_cases,
@@ -168,7 +168,7 @@ def test_debye_waller_without_per_layer_overrides_keeps_single_sigma() -> None:
 
 def test_rcwa_simulation_runs_for_multiple_energies() -> None:
     grating = build_test_grating()
-    simulation = RCWASimulation(
+    simulation = GratingSimulation(
         grating=grating,
         diffraction_order=1,
         fourier_orders=25,
@@ -187,7 +187,7 @@ def test_rcwa_simulation_runs_for_multiple_energies() -> None:
 
 def test_rcwa_simulation_runs_laminar_grating_end_to_end() -> None:
     grating = build_test_grating()
-    simulation = RCWASimulation(
+    simulation = GratingSimulation(
         grating=grating,
         diffraction_order=1,
         fourier_orders=5,
@@ -203,7 +203,7 @@ def test_rcwa_simulation_runs_laminar_grating_end_to_end() -> None:
 
 def test_rcwa_simulation_loads_experimental_data_and_plots_comparison(tmp_path: Path) -> None:
     grating = build_test_grating()
-    simulation = RCWASimulation(
+    simulation = GratingSimulation(
         grating=grating,
         diffraction_order=1,
         fourier_orders=25,
@@ -734,7 +734,7 @@ def fake_run_simulation(**kwargs: object) -> SingleSimulationResult:
 
     monkeypatch.setattr(simulation_module, "run_simulation", fake_run_simulation)
     grating = build_test_grating()
-    runner = BatchSimulationRunner(default_fourier_orders=5)
+    runner = BatchSimulationRunner(fourier_orders=5)
 
     def case_generator() -> Iterator[dict[str, object]]:
         yield {
@@ -1133,7 +1133,7 @@ def test_batch_runner_rejects_unsupported_material_input_in_fail_fast_mode() ->
         top_cap_thickness_nm=0.7,
     )
     runner = BatchSimulationRunner(
-        default_fourier_orders=5,
+        fourier_orders=5,
         on_error="fail_fast",
     )
 
@@ -1302,7 +1302,7 @@ def fake_run_simulation(**kwargs: object) -> SingleSimulationResult:
 def test_batch_runner_parallel_executes_cases_and_writes_checkpoint(tmp_path: Path) -> None:
     grating = build_test_grating()
     runner = BatchSimulationRunner(
-        default_fourier_orders=1,
+        fourier_orders=1,
         max_workers=2,
         checkpoint_dir=tmp_path,
         on_error="continue",
@@ -1347,7 +1347,7 @@ def test_batch_runner_parallel_resume_skips_completed_cases(tmp_path: Path) -> N
         encoding="utf-8",
     )
     runner = BatchSimulationRunner(
-        default_fourier_orders=1,
+        fourier_orders=1,
         max_workers=2,
         checkpoint_dir=tmp_path,
         resume=True,
@@ -1380,7 +1380,7 @@ def test_parallel_worker_is_top_level_and_spawn_compatible() -> None:
 
 
 def test_rcwa_simulation_raises_for_non_physical_efficiency() -> None:
-    simulation = RCWASimulation(grating=build_test_grating())
+    simulation = GratingSimulation(grating=build_test_grating())
 
     with pytest.raises(ValueError, match="Non-physical reflected diffraction efficiency"):
         simulation._validate_reflected_efficiencies(
diff --git a/tests/unit/test_simulation_theta_search.py b/tests/unit/test_simulation_theta_search.py
index 36a9e1a..7e7d8cd 100644
--- a/tests/unit/test_simulation_theta_search.py
+++ b/tests/unit/test_simulation_theta_search.py
@@ -208,7 +208,7 @@ def fake_run_case_payload(
     )
 
     assert len(payloads) == 1
-    assert payloads[0]["min_efficiency"] == pytest.approx(-0.125)
+    assert payloads[0]["min_reflected_efficiency"] == pytest.approx(-0.125)
     assert payloads[0]["max_total_reflected_efficiency"] == pytest.approx(1.05)
 
 
diff --git a/tests/unit/test_web_app.py b/tests/unit/test_web_app.py
index 727074f..aa7bb20 100644
--- a/tests/unit/test_web_app.py
+++ b/tests/unit/test_web_app.py
@@ -2292,3 +2292,95 @@ def fake_run_cases(self, cases, metadata=None):  # type: ignore[no-untyped-def]
     saved_manifest = json.loads(manifests[0].read_text(encoding="utf-8"))
     assert saved_manifest["figure_json"]
     assert saved_manifest["plot_config"]["series_styles"]
+
+
+def test_parameter_study_run_uses_selected_solver(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+) -> None:
+    """Verify the run form's solver choice reaches the parameter-study call."""
+
+    pytest.importorskip("flask")
+
+    from grax.web.app import create_app
+
+    captured: dict[str, object] = {}
+
+    def fake_run_parameter_study(**kwargs):  # type: ignore[no-untyped-def]
+        captured.update(kwargs)
+        return SimpleNamespace()
+
+    def fake_plot_parameter_study(result, output_filename):  # type: ignore[no-untyped-def]
+        Path(output_filename).write_text("plot", encoding="utf-8")
+
+    monkeypatch.setattr("grax.parameter_sweep.run_parameter_study", fake_run_parameter_study)
+    monkeypatch.setattr("grax.parameter_sweep.plot_parameter_study", fake_plot_parameter_study)
+
+    app = create_app(data_dir=tmp_path)
+    client = app.test_client()
+    client.post(
+        "/gratings",
+        data={
+            "name": "Solver grating",
+            "grating_type": "blazed",
+            "period_lpermm": "600",
+            "x_resolution_nm": "2.0",
+            "z_resolution_nm": "0.5",
+            "blaze_angle_deg": "0.75",
+            "anti_blaze_angle_deg": "",
+            "stack_type": "single_layer",
+            "substrate_material": "Si",
+            "layer_material": "Au",
+            "layer_thickness_nm": "30.0",
+        },
+    )
+    grating_id = GratingStore(tmp_path / "saved_gratings").list()[0]["id"]
+
+    response = client.post(
+        f"/gratings/{grating_id}/runs",
+        data={
+            "workflow": "parameter_study",
+            "energy_start_ev": "100",
+            "energy_stop_ev": "120",
+            "energy_points": "3",
+            "grazing_angle_deg": "1.5",
+            "diffraction_order": "1",
+            "fourier_orders": "5",
+            "polarization": "p",
+            "solver": "neviere",
+            "run_x_resolution_nm": "0.75",
+            "run_z_resolution_nm": "0.25",
+        },
+        follow_redirects=False,
+    )
+
+    assert response.status_code == 302
+    run_id = response.headers["Location"].rsplit("/", 1)[-1]
+    manifest_path = tmp_path / "runs" / run_id / "manifest.json"
+
+    deadline = time.monotonic() + 2.0
+    manifest: dict[str, object] = {}
+    while time.monotonic() < deadline:
+        if captured:
+            manifest = json.loads(manifest_path.read_text())
+            if manifest.get("status") == "completed":
+                break
+        time.sleep(0.02)
+
+    assert captured["solver"] == "neviere"
+    assert manifest.get("solver") == "neviere"
+    assert manifest.get("run_input", {}).get("solver") == "neviere"
+
+
+def test_run_form_rejects_an_unknown_solver(tmp_path: Path) -> None:
+    """Verify an invalid solver name is refused rather than silently defaulted."""
+
+    pytest.importorskip("flask")
+
+    from grax.web.app import _normalized_solver
+
+    assert _normalized_solver("neviere") == "neviere"
+    assert _normalized_solver(None) == "rcwa"
+    assert _normalized_solver("  RCWA  ") == "rcwa"
+    with pytest.raises(ValueError, match="solver must be"):
+        _normalized_solver("differential")
diff --git a/tools/build_docs.sh b/tools/build_docs.sh
index bb53769..e5c7f27 100755
--- a/tools/build_docs.sh
+++ b/tools/build_docs.sh
@@ -39,11 +39,26 @@ if [[ "${EXPLICIT_BUILD_SELECTION}" == false ]]; then
         BUILD_HTML=true
     else
         BUILD_HTML=true
-        BUILD_LATEX=true
-        BUILD_PDF=true
+        if command -v pdflatex >/dev/null 2>&1 && command -v make >/dev/null 2>&1; then
+            BUILD_LATEX=true
+            BUILD_PDF=true
+        else
+            echo "Warning: pdflatex and/or make are unavailable; building HTML only."
+            echo "Install a LaTeX distribution and rerun with --pdf to build the PDF."
+        fi
     fi
 fi
 
+if [[ "${BUILD_PDF}" == true ]] && ! command -v pdflatex >/dev/null 2>&1; then
+    echo "Error: --pdf requires pdflatex. Install a LaTeX distribution first."
+    exit 1
+fi
+
+if [[ "${BUILD_PDF}" == true ]] && ! command -v make >/dev/null 2>&1; then
+    echo "Error: --pdf requires make. Install make first."
+    exit 1
+fi
+
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
 PROJECT_ROOT="$(cd "${SCRIPT_DIR}/.." && pwd)"
 DOCS_DIR="${PROJECT_ROOT}/docs"
@@ -140,20 +155,19 @@ if [[ "${SKIP_IMAGE_SYNC}" == false ]]; then
     cp "${PROJECT_ROOT}/examples/grating/results/afm_preprocessing_laminar/04_periodicity_ramp.png" \
       "${GRATING_IMAGE_DIR}/afm_preprocessing_laminar/04_periodicity_ramp.png"
 
-    cp "${PROJECT_ROOT}/examples/simulation/batch_user_cases/results/batch_user_cases_orders_1_3_vs_depth.png" \
+    cp "${PROJECT_ROOT}/examples/simulation/batch_user_cases/results/batch_user_cases_orders_1_3_vs_depth_rcwa.png" \
       "${SIM_IMAGE_DIR}/batch_user_cases_orders_1_3_vs_depth.png"
-    cp "${PROJECT_ROOT}/examples/simulation/fixed_angle_sweep/results/fixed_angle_orders_1_3.png" \
+    cp "${PROJECT_ROOT}/examples/simulation/fixed_angle_sweep/results/fixed_angle_orders_1_3_rcwa.png" \
       "${SIM_IMAGE_DIR}/fixed_angle_orders_1_3.png"
-    # Copy the roughness comparison plot generated by the fixed_angle_roughness example.
-    cp "${PROJECT_ROOT}/examples/simulation/fixed_angle_roughness/results/fixed_angle_roughness_order1_comparison.png" \
+    cp "${PROJECT_ROOT}/examples/simulation/fixed_angle_roughness/plots_roughness_kind_comparison/roughness_kind_comparison_order1_comparison.png" \
       "${SIM_IMAGE_DIR}/fixed_angle_roughness_order1_comparison.png"
-    cp "${PROJECT_ROOT}/examples/simulation/monochromator_sweep/results/monochromator_orders_1_3.png" \
+    cp "${PROJECT_ROOT}/examples/simulation/monochromator_sweep/results/monochromator_orders_1_3_rcwa.png" \
       "${SIM_IMAGE_DIR}/monochromator_orders_1_3.png"
-    cp "${PROJECT_ROOT}/examples/simulation/energy_angle_sweep/results/energy_angle_multilayer_fast.png" \
+    cp "${PROJECT_ROOT}/examples/simulation/energy_angle_sweep/results/energy_angle_multilayer_fast_rcwa.png" \
       "${SIM_IMAGE_DIR}/energy_angle_multilayer_fast.png"
     cp "${PROJECT_ROOT}/examples/simulation/multilayer_theta_search/results/multilayer_theta_search_workflow.png" \
       "${SIM_IMAGE_DIR}/multilayer_theta_search_workflow.png"
-    cp "${PROJECT_ROOT}/examples/simulation/parameter_study/results/parameter_study_grid.png" \
+    cp "${PROJECT_ROOT}/examples/simulation/parameter_study/results/parameter_study_grid_rcwa.png" \
       "${SIM_IMAGE_DIR}/parameter_study_grid.png"
     cp "${PROJECT_ROOT}/examples/optimizer/optimizer_laminar/results/laminar_fit/best_fit.png" \
       "${OPTIMIZER_IMAGE_DIR}/best_fit.png"
@@ -176,7 +190,7 @@ if [[ "${SKIP_IMAGE_SYNC}" == false ]]; then
     cp "${PROJECT_ROOT}/tools/numba_speed/results/multi_energy_multilayer_numba_vs_legacy_plots.png" \
       "${NUMBA_SPEED_IMAGE_DIR}/multi_energy_multilayer_numba_vs_legacy_plots.png"
 
-    cp "${PROJECT_ROOT}/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_all_orders.csv" \
+    cp "${PROJECT_ROOT}/examples/simulation/blazed_multilayer_sweep/results/blazed_multilayer_all_orders_rcwa.csv" \
       "${PROJECT_ROOT}/validation/blazed_multilayer/simulation/grax_multilayer_theta_search_all_orders.csv"
     (
       cd "${PROJECT_ROOT}/validation/blazed_multilayer"
@@ -210,6 +224,31 @@ if [[ "${SKIP_IMAGE_SYNC}" == false ]]; then
       "${COMPARISON_IMAGE_DIR}/laminar_150lmm_monochromator_profile.png"
     cp "${PROJECT_ROOT}/validation/laminar_150lmm/comparison_laminar_150lmm_monochromator.png" \
       "${COMPARISON_IMAGE_DIR}/comparison_laminar_150lmm_monochromator.png"
+
+    # Solver comparison figures, produced by validation/compare_solvers.py after
+    # running each sweep with --solver rcwa --tag rerun and --solver neviere.
+    # Copied only when present so a docs build does not require those runs.
+    for solver_comparison in \
+      "laminar/results/laminar_fixed_angle_all_orders_solver_comparison.png" \
+      "blazed/results/blazed_comparison_monochromator_orders_1_3_solver_comparison.png" \
+      "laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_solver_comparison.png" \
+      "blazed_multilayer/results/blazed_multilayer_all_orders_solver_comparison.png"; do
+        source_path="${PROJECT_ROOT}/validation/${solver_comparison}"
+        if [[ -f "${source_path}" ]]; then
+            cp "${source_path}" "${COMPARISON_IMAGE_DIR}/$(basename "${source_path}")"
+        else
+            echo "  skipping missing solver comparison: ${solver_comparison}"
+        fi
+    done
+
+    cp "${PROJECT_ROOT}/examples/simulation/neviere_solver/results/neviere_solver_comparison.png" \
+      "${SIM_IMAGE_DIR}/neviere_solver_comparison.png"
+    cp "${PROJECT_ROOT}/examples/simulation/deep_grating_limits/results/deep_grating_limits_p.png" \
+      "${SIM_IMAGE_DIR}/deep_grating_limits_p.png"
+    cp "${PROJECT_ROOT}/examples/simulation/continuous_vs_staircase/results/continuous_vs_staircase_p.png" \
+      "${SIM_IMAGE_DIR}/continuous_vs_staircase_p.png"
+    cp "${PROJECT_ROOT}/examples/simulation/solver_runtime/results/solver_runtime_full.png" \
+      "${SIM_IMAGE_DIR}/solver_runtime_full.png"
     echo
 fi
 
diff --git a/tools/solver_comparison/_helpers.py b/tools/solver_comparison/_helpers.py
new file mode 100644
index 0000000..712e459
--- /dev/null
+++ b/tools/solver_comparison/_helpers.py
@@ -0,0 +1,462 @@
+"""Shared helpers for running validation sweeps with either solver.
+
+Every validation sweep script accepts ``--solver`` and ``--stride``. With no
+flags a script behaves exactly as before and writes to its historical output
+paths, so the checked-in RCWA artifacts stay reproducible. ``--solver neviere``
+writes to ``*_neviere.*`` siblings instead, which lets both solvers' results sit
+next to each other and be compared per diffraction order.
+"""
+
+from __future__ import annotations
+
+import argparse
+import sys
+from dataclasses import dataclass
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+
+SOLVER_CHOICES = ("rcwa", "neviere")
+
+#: Human-readable labels used in comparison plots and tables.
+SOLVER_LABELS = {"rcwa": "RCWA (modal)", "neviere": "Nevière (differential)"}
+
+
+def add_solver_arguments(parser: argparse.ArgumentParser) -> argparse.ArgumentParser:
+    """Add the shared solver-selection arguments to one script's parser.
+
+    Args:
+        parser: Parser to extend.
+
+    Returns:
+        The same parser, for chaining.
+    """
+
+    parser.add_argument(
+        "--solver",
+        choices=SOLVER_CHOICES,
+        default="rcwa",
+        help="Electromagnetic solver to run (default: rcwa, matching the checked-in results).",
+    )
+    parser.add_argument(
+        "--stride",
+        type=int,
+        default=1,
+        help="Keep every Nth sweep point. Use to subsample an expensive sweep.",
+    )
+    parser.add_argument(
+        "--tag",
+        default="",
+        help=(
+            "Extra suffix appended to every output path, on top of the solver "
+            "suffix. Use to write a fresh run alongside the checked-in artifacts "
+            "instead of overwriting them, e.g. --tag rerun."
+        ),
+    )
+    return parser
+
+
+def solver_suffix(solver: str) -> str:
+    """Return the output-path suffix for one solver.
+
+    The RCWA suffix is empty so existing artifact paths are untouched.
+
+    Args:
+        solver: Solver name.
+
+    Returns:
+        Suffix to insert before a file extension.
+    """
+
+    if solver not in SOLVER_CHOICES:
+        raise ValueError(f"solver must be one of {SOLVER_CHOICES}, got {solver!r}.")
+    return "" if solver == "rcwa" else f"_{solver}"
+
+
+def solver_output_path(path: Path, solver: str, tag: str = "") -> Path:
+    """Return one output path rewritten for the given solver.
+
+    Args:
+        path: Historical (RCWA) output path.
+        solver: Solver name.
+        tag: Optional extra suffix, so a fresh run can be written alongside the
+            checked-in artifacts rather than over them.
+
+    Returns:
+        Path with the solver suffix and tag inserted before the extension.
+    """
+
+    suffix = solver_suffix(solver)
+    if tag:
+        suffix = f"{suffix}_{tag.strip('_')}"
+    if not suffix:
+        return path
+    return path.with_name(f"{path.stem}{suffix}{path.suffix}")
+
+
+def apply_stride(values, stride: int):
+    """Return every ``stride``-th element of a sweep axis.
+
+    Args:
+        values: Sequence or array of sweep points.
+        stride: Keep every Nth point. Must be >= 1.
+
+    Returns:
+        The subsampled sequence, of the same type where practical.
+    """
+
+    if stride < 1:
+        raise ValueError("stride must be >= 1.")
+    if stride == 1:
+        return values
+    if isinstance(values, np.ndarray):
+        return values[::stride]
+    return list(values)[::stride]
+
+
+def load_all_orders_csv(path: Path) -> pd.DataFrame:
+    """Load one ``write_all_orders_csv`` output.
+
+    Args:
+        path: CSV path.
+
+    Returns:
+        DataFrame with energy, order, efficiency, and diffraction angle.
+    """
+
+    frame = pd.read_csv(path)
+    frame["order"] = frame["order"].astype(float)
+    return frame
+
+
+def compare_all_orders(
+    rcwa_csv: Path,
+    neviere_csv: Path,
+    *,
+    orders: list[int],
+) -> pd.DataFrame:
+    """Return a per-order deviation table between two solver runs.
+
+    Only energies present in both runs are compared, so a subsampled
+    differential-method run can still be checked against a full RCWA sweep.
+
+    Args:
+        rcwa_csv: All-orders CSV from the RCWA run.
+        neviere_csv: All-orders CSV from the differential-method run.
+        orders: Positive diffraction orders to compare. The solver reports the
+            reflected orders with a negative sign, matching
+            :func:`grax.efficiency_for_order`.
+
+    Returns:
+        One row per requested order with the shared point count and the maximum,
+        mean, and RMS absolute deviation, plus the maximum deviation relative to
+        the peak RCWA efficiency of that order.
+    """
+
+    rcwa = load_all_orders_csv(rcwa_csv)
+    neviere = load_all_orders_csv(neviere_csv)
+
+    rows = []
+    for order in orders:
+        rcwa_order = rcwa[np.isclose(rcwa["order"], -order)][["energy_ev", "efficiency"]]
+        neviere_order = neviere[np.isclose(neviere["order"], -order)][["energy_ev", "efficiency"]]
+        merged = rcwa_order.merge(
+            neviere_order,
+            on="energy_ev",
+            suffixes=("_rcwa", "_neviere"),
+        )
+        if merged.empty:
+            rows.append(
+                {
+                    "order": order,
+                    "shared_points": 0,
+                    "max_abs_deviation": float("nan"),
+                    "mean_abs_deviation": float("nan"),
+                    "rms_deviation": float("nan"),
+                    "peak_rcwa_efficiency": float("nan"),
+                    "max_deviation_over_peak": float("nan"),
+                }
+            )
+            continue
+
+        deviation = np.abs(
+            merged["efficiency_rcwa"].to_numpy() - merged["efficiency_neviere"].to_numpy()
+        )
+        peak = float(np.max(np.abs(merged["efficiency_rcwa"].to_numpy())))
+        rows.append(
+            {
+                "order": order,
+                "shared_points": int(len(merged)),
+                "max_abs_deviation": float(np.max(deviation)),
+                "mean_abs_deviation": float(np.mean(deviation)),
+                "rms_deviation": float(np.sqrt(np.mean(deviation**2))),
+                "peak_rcwa_efficiency": peak,
+                "max_deviation_over_peak": (
+                    float(np.max(deviation) / peak) if peak > 0 else float("nan")
+                ),
+            }
+        )
+    return pd.DataFrame(rows)
+
+
+def plot_solver_comparison(
+    rcwa_csv: Path,
+    neviere_csv: Path,
+    output_path: Path,
+    *,
+    orders: list[int],
+    title: str,
+) -> None:
+    """Save a side-by-side solver comparison with a deviation panel.
+
+    Args:
+        rcwa_csv: All-orders CSV from the RCWA run.
+        neviere_csv: All-orders CSV from the differential-method run.
+        output_path: Output image path.
+        orders: Positive diffraction orders to overlay.
+        title: Plot title.
+    """
+
+    import matplotlib.pyplot as plt
+
+    rcwa = load_all_orders_csv(rcwa_csv)
+    neviere = load_all_orders_csv(neviere_csv)
+
+    figure, axes = plt.subplots(
+        2,
+        1,
+        figsize=(11, 8),
+        sharex=True,
+        gridspec_kw={"height_ratios": [2.4, 1.0]},
+    )
+    efficiency_axis, deviation_axis = axes
+    colors = plt.rcParams["axes.prop_cycle"].by_key()["color"]
+
+    for index, order in enumerate(orders):
+        color = colors[index % len(colors)]
+        rcwa_order = rcwa[np.isclose(rcwa["order"], -order)].sort_values("energy_ev")
+        neviere_order = neviere[np.isclose(neviere["order"], -order)].sort_values("energy_ev")
+        efficiency_axis.plot(
+            rcwa_order["energy_ev"],
+            rcwa_order["efficiency"],
+            "-",
+            color=color,
+            linewidth=1.4,
+            label=f"order {order} - {SOLVER_LABELS['rcwa']}",
+        )
+        efficiency_axis.plot(
+            neviere_order["energy_ev"],
+            neviere_order["efficiency"],
+            "--",
+            color=color,
+            linewidth=1.4,
+            dashes=(4, 3),
+            label=f"order {order} - {SOLVER_LABELS['neviere']}",
+        )
+
+        merged = rcwa_order[["energy_ev", "efficiency"]].merge(
+            neviere_order[["energy_ev", "efficiency"]],
+            on="energy_ev",
+            suffixes=("_rcwa", "_neviere"),
+        )
+        if merged.empty:
+            continue
+        deviation_axis.semilogy(
+            merged["energy_ev"],
+            np.abs(merged["efficiency_rcwa"] - merged["efficiency_neviere"]),
+            "-",
+            color=color,
+            linewidth=1.0,
+            label=f"order {order}",
+        )
+
+    efficiency_axis.set_ylabel("Diffraction efficiency")
+    efficiency_axis.set_title(title)
+    efficiency_axis.grid(True, alpha=0.3)
+    efficiency_axis.legend(loc="best", fontsize=8)
+
+    deviation_axis.set_xlabel("Photon energy (eV)")
+    deviation_axis.set_ylabel("|RCWA - Nevière|")
+    deviation_axis.grid(True, alpha=0.3, which="both")
+    deviation_axis.legend(loc="best", fontsize=8)
+
+    figure.tight_layout()
+    figure.savefig(output_path, dpi=150, bbox_inches="tight")
+    plt.close(figure)
+
+
+def write_solver_comparison(
+    *,
+    rcwa_csv: Path,
+    neviere_csv: Path,
+    summary_csv: Path,
+    plot_path: Path,
+    orders: list[int],
+    title: str,
+) -> pd.DataFrame:
+    """Write the comparison table and plot for one validation case.
+
+    Args:
+        rcwa_csv: All-orders CSV from the RCWA run.
+        neviere_csv: All-orders CSV from the differential-method run.
+        summary_csv: Destination for the per-order deviation table.
+        plot_path: Destination for the comparison figure.
+        orders: Positive diffraction orders to compare.
+        title: Plot title.
+
+    Returns:
+        The per-order deviation table.
+    """
+
+    for path in (rcwa_csv, neviere_csv):
+        if not path.exists():
+            raise FileNotFoundError(
+                f"{path} is missing. Run the sweep for both solvers before comparing:\n"
+                f"  python <sweep script>\n"
+                f"  python <sweep script> --solver neviere"
+            )
+
+    summary = compare_all_orders(rcwa_csv, neviere_csv, orders=orders)
+    summary_csv.parent.mkdir(parents=True, exist_ok=True)
+    summary.to_csv(summary_csv, index=False)
+    plot_solver_comparison(rcwa_csv, neviere_csv, plot_path, orders=orders, title=title)
+    return summary
+
+
+def print_solver_comparison(summary: pd.DataFrame, *, title: str) -> None:
+    """Print one comparison table in a readable fixed-width form.
+
+    Args:
+        summary: Table returned by :func:`compare_all_orders`.
+        title: Heading printed above the table.
+    """
+
+    print(f"\n{title}")
+    print(f"{'order':>6} {'points':>7} {'max|dE|':>12} {'mean|dE|':>12} "
+          f"{'rms':>12} {'peak E':>12} {'max|dE|/peak':>14}")
+    for _, row in summary.iterrows():
+        print(
+            f"{int(row['order']):>6} {int(row['shared_points']):>7} "
+            f"{row['max_abs_deviation']:>12.3e} {row['mean_abs_deviation']:>12.3e} "
+            f"{row['rms_deviation']:>12.3e} {row['peak_rcwa_efficiency']:>12.3e} "
+            f"{row['max_deviation_over_peak']:>14.3e}"
+        )
+
+
+def validation_root_on_path() -> Path:
+    """Add the validation root to ``sys.path`` and return it.
+
+    Sweep scripts run as plain files rather than as a package, so they import
+    this module by first putting its directory on the path.
+    """
+
+    root = Path(__file__).resolve().parent
+    if str(root) not in sys.path:
+        sys.path.insert(0, str(root))
+    return root
+
+
+#: Legend labels for the two grax curves in the external-code comparison plots.
+GRAX_CURVE_LABELS = {"rcwa": "graxpy (RCWA)", "neviere": "graxpy (Nevière DM)"}
+
+#: Per-solver line styles. The two solvers agree to ~1e-11, so without a dashed
+#: overlay the second curve hides the first completely and the plot looks as
+#: though one of them is missing.
+GRAX_CURVE_STYLES: dict[str, dict[str, object]] = {
+    "rcwa": {"linestyle": "-"},
+    "neviere": {"linestyle": (0, (6, 4))},
+}
+
+
+@dataclass(frozen=True)
+class GraxCurve:
+    """One solver's efficiency curve for a validation case.
+
+    Attributes:
+        solver: Solver name.
+        label: Legend label.
+        energy_ev: Photon energies.
+        efficiency: Efficiencies aligned with ``energy_ev``.
+        source: CSV the curve was read from.
+        style: Matplotlib keyword arguments that keep overlapping curves legible.
+    """
+
+    solver: str
+    label: str
+    energy_ev: pd.Series
+    efficiency: pd.Series
+    source: Path
+    style: dict[str, object]
+
+
+def resolve_solver_csv(base_csv: Path, solver: str) -> Path | None:
+    """Return the all-orders CSV to plot for one solver, or ``None`` if absent.
+
+    For ``"rcwa"`` a same-revision ``*_rerun.csv`` is preferred over the
+    checked-in artifact when one exists. That matters: the committed RCWA CSVs
+    predate several solver changes, so pairing a fresh differential-method run
+    against them would show that drift as though it were a difference between
+    the two methods.
+
+    Args:
+        base_csv: Historical (RCWA) all-orders CSV path for the case.
+        solver: Solver name.
+
+    Returns:
+        Path to the CSV to plot, or ``None`` when that solver has not been run.
+    """
+
+    if solver == "rcwa":
+        for candidate in (solver_output_path(base_csv, "rcwa", "rerun"), base_csv):
+            if candidate.exists():
+                return candidate
+        return None
+    candidate = solver_output_path(base_csv, solver)
+    return candidate if candidate.exists() else None
+
+
+def load_grax_curves(
+    base_csv: Path,
+    *,
+    order: int,
+    solvers: tuple[str, ...] = SOLVER_CHOICES,
+) -> list[GraxCurve]:
+    """Return one plottable curve per solver that has been run for this case.
+
+    Missing solver runs are skipped rather than raising, so a comparison script
+    still works before the differential-method sweep has been run.
+
+    Args:
+        base_csv: Historical (RCWA) all-orders CSV path for the case.
+        order: Signed diffraction order to extract, as stored in the CSV
+            (reflected orders are negative).
+        solvers: Solvers to look for, in plot order.
+
+    Returns:
+        One :class:`GraxCurve` per available solver, in ``solvers`` order.
+    """
+
+    curves: list[GraxCurve] = []
+    for solver in solvers:
+        path = resolve_solver_csv(base_csv, solver)
+        if path is None:
+            print(f"  note: no {solver} results for {base_csv.name}, skipping that curve")
+            continue
+        frame = load_all_orders_csv(path)
+        selected = frame[np.isclose(frame["order"], order)].sort_values("energy_ev")
+        if selected.empty:
+            print(f"  note: {path.name} has no order {order}, skipping that curve")
+            continue
+        print(f"  {GRAX_CURVE_LABELS[solver]:<22} <- {path.name}  ({len(selected)} points)")
+        curves.append(
+            GraxCurve(
+                solver=solver,
+                label=GRAX_CURVE_LABELS[solver],
+                energy_ev=selected["energy_ev"],
+                efficiency=selected["efficiency"],
+                source=path,
+                style=dict(GRAX_CURVE_STYLES[solver]),
+            )
+        )
+    return curves
diff --git a/tools/solver_comparison/compare_solvers.py b/tools/solver_comparison/compare_solvers.py
new file mode 100644
index 0000000..267e95f
--- /dev/null
+++ b/tools/solver_comparison/compare_solvers.py
@@ -0,0 +1,161 @@
+"""Internal cross-check of the two solvers on the validation cases.
+
+Developer tool, not part of the documented validation workflow. It quantifies
+how far the RCWA and Nevière differential-method results drift apart, which is
+useful when changing either solver but is not something a user needs to run.
+
+Run each sweep with both solvers first, then this script:
+
+    python validation/laminar/run_rcwa.py
+    python validation/laminar/run_neviere.py
+    python tools/solver_comparison/compare_solvers.py --case laminar
+
+It writes a per-order deviation table and a side-by-side plot with a difference
+panel into each case's ``results/`` directory. Both sides must come from the same
+code revision, so it reads the ``*_rcwa.csv`` written by ``run_rcwa.py`` rather
+than the older checked-in artifact, and separately reports how far that artifact
+has drifted.
+"""
+
+from __future__ import annotations
+
+import argparse
+import sys
+from dataclasses import dataclass
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+from _helpers import (  # noqa: E402
+    print_solver_comparison,
+    write_solver_comparison,
+)
+
+VALIDATION_ROOT = Path(__file__).resolve().parents[2] / "validation"
+
+
+@dataclass(frozen=True)
+class ValidationCase:
+    """One validation sweep that can be run with either solver.
+
+    Attributes:
+        name: Short case identifier used on the command line.
+        title: Human-readable title for the plot.
+        results_dir: Directory holding the sweep's result artifacts.
+        stem: Base filename of the all-orders CSV, without suffix or extension.
+        orders: Positive diffraction orders to compare.
+    """
+
+    name: str
+    title: str
+    results_dir: Path
+    stem: str
+    orders: tuple[int, ...]
+
+    @property
+    def rcwa_csv(self) -> Path:
+        """Return the path of the current-code RCWA all-orders CSV."""
+
+        return self.results_dir / f"{self.stem}_rcwa.csv"
+
+    @property
+    def neviere_csv(self) -> Path:
+        """Return the path of the differential-method all-orders CSV."""
+
+        return self.results_dir / f"{self.stem}_neviere.csv"
+
+    @property
+    def committed_rcwa_csv(self) -> Path:
+        """Return the path of the checked-in RCWA all-orders CSV."""
+
+        return self.results_dir / f"{self.stem}.csv"
+
+
+CASES = (
+    ValidationCase(
+        name="laminar",
+        title="Laminar 400 l/mm, fixed 4 deg grazing, p polarization",
+        results_dir=VALIDATION_ROOT / "laminar" / "results",
+        stem="laminar_fixed_angle_all_orders",
+        orders=(1, 2, 3),
+    ),
+    ValidationCase(
+        name="blazed",
+        title="Blazed 600 l/mm monochromator, cff 2.25, p polarization",
+        results_dir=VALIDATION_ROOT / "blazed" / "results",
+        stem="blazed_comparison_monochromator_orders_1_3",
+        orders=(1, 2, 3),
+    ),
+    ValidationCase(
+        name="laminar_150lmm",
+        title="Laminar 150 l/mm monochromator, cff 1.45, p polarization",
+        results_dir=VALIDATION_ROOT / "laminar_150lmm" / "results",
+        stem="laminar_150lmm_monochromator_all_orders",
+        orders=(1, 2, 3),
+    ),
+    ValidationCase(
+        name="blazed_multilayer",
+        title="Blazed 2400 l/mm on Cr/C multilayer, energy-angle pairs, p polarization",
+        results_dir=VALIDATION_ROOT / "blazed_multilayer" / "results",
+        stem="blazed_multilayer_all_orders",
+        orders=(1, 2, 3),
+    ),
+)
+
+
+def main() -> int:
+    """Write comparison artifacts for every case with results from both solvers."""
+
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument(
+        "--case",
+        choices=[case.name for case in CASES],
+        action="append",
+        help="Limit to one case. Repeatable. Defaults to every case.",
+    )
+    arguments = parser.parse_args()
+    selected = [case for case in CASES if not arguments.case or case.name in arguments.case]
+
+    missing: list[str] = []
+    for case in selected:
+        if not case.rcwa_csv.exists() or not case.neviere_csv.exists():
+            absent = [
+                str(path.relative_to(VALIDATION_ROOT))
+                for path in (case.rcwa_csv, case.neviere_csv)
+                if not path.exists()
+            ]
+            missing.append(f"{case.name}: missing {', '.join(absent)}")
+            continue
+
+        summary = write_solver_comparison(
+            rcwa_csv=case.rcwa_csv,
+            neviere_csv=case.neviere_csv,
+            summary_csv=case.results_dir / f"{case.stem}_solver_comparison.csv",
+            plot_path=case.results_dir / f"{case.stem}_solver_comparison.png",
+            orders=list(case.orders),
+            title=case.title,
+        )
+        print_solver_comparison(summary, title=case.title)
+
+        if case.committed_rcwa_csv.exists():
+            from _helpers import compare_all_orders
+
+            drift = compare_all_orders(
+                case.committed_rcwa_csv,
+                case.rcwa_csv,
+                orders=list(case.orders),
+            )
+            print_solver_comparison(
+                drift,
+                title="  (for reference: checked-in RCWA artifact vs current-code RCWA)",
+            )
+
+    if missing:
+        print("\nSkipped:")
+        for line in missing:
+            print(f"  {line}")
+        print("Run each sweep with --solver rcwa  and --solver neviere first.")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/blazed/comparison_blazed_monochromator_sweep.png b/validation/blazed/comparison_blazed_monochromator_sweep.png
index 86c2118..e184ce9 100644
Binary files a/validation/blazed/comparison_blazed_monochromator_sweep.png and b/validation/blazed/comparison_blazed_monochromator_sweep.png differ
diff --git a/validation/blazed/comparison_blazed_monochromator_sweep.py b/validation/blazed/comparison_blazed_monochromator_sweep.py
index fa55f61..d468410 100644
--- a/validation/blazed/comparison_blazed_monochromator_sweep.py
+++ b/validation/blazed/comparison_blazed_monochromator_sweep.py
@@ -6,6 +6,54 @@
 import pandas as pd
 import matplotlib.pyplot as plt
 
+
+# Both solvers' results are plotted when present. A fresh run writes
+# ``*_rcwa.csv`` / ``*_neviere.csv``; the unsuffixed CSV is the older checked-in
+# artifact and is only used as a fallback, because it predates several solver
+# changes and pairing it against a fresh run would show that drift as though it
+# were a difference between the two methods.
+SOLVER_LABELS = {"rcwa": "graxpy (RCWA)", "neviere": "graxpy (Nevière DM)"}
+# The two solvers agree to ~1e-11, so without a dashed overlay the second curve
+# hides the first completely and the plot looks as though one is missing.
+SOLVER_STYLES = {"rcwa": {"linestyle": "-"}, "neviere": {"linestyle": (0, (6, 4))}}
+
+
+def load_solver_curves(base_csv, order):
+    """Return (label, energy, efficiency, style) for each solver that has been run.
+
+    Args:
+        base_csv: Historical unsuffixed all-orders CSV path for this case.
+        order: Signed diffraction order to extract (reflected orders are negative).
+
+    Returns:
+        List of plottable curves, skipping solvers with no results yet.
+    """
+
+    curves = []
+    for solver in ("rcwa", "neviere"):
+        candidates = [base_csv.with_name(f"{base_csv.stem}_{solver}{base_csv.suffix}")]
+        if solver == "rcwa":
+            candidates.append(base_csv)
+        path = next((candidate for candidate in candidates if candidate.exists()), None)
+        if path is None:
+            print(f"  note: no {solver} results yet, skipping that curve")
+            continue
+        frame = pd.read_csv(path)
+        selected = frame[frame["order"] == order].sort_values("energy_ev")
+        if selected.empty:
+            print(f"  note: {path.name} has no order {order}, skipping that curve")
+            continue
+        print(f"  {SOLVER_LABELS[solver]:<22} <- {path.name}  ({len(selected)} points)")
+        curves.append(
+            (
+                SOLVER_LABELS[solver],
+                selected["energy_ev"],
+                selected["efficiency"],
+                dict(SOLVER_STYLES[solver]),
+            )
+        )
+    return curves
+
 base_path = Path(__file__).resolve().parent
 
 
@@ -22,11 +70,12 @@
 meas_energy = meas["energy"]
 meas_eff = meas["eff"]
 
-# Load grax results (current)
-ret = pd.read_csv(base_path / "results" / "blazed_comparison_monochromator_orders_1_3.csv")
-ret_m1 = ret[ret["order"] == -1].sort_values("energy_ev")
-ret_energy = ret_m1["energy_ev"]
-ret_eff = ret_m1["efficiency"]
+# Load grax results, one curve per solver that has been run
+print("graxpy curves:")
+grax_curves = load_solver_curves(
+    base_path / "results" / "blazed_comparison_monochromator_orders_1_3.csv",
+    order=-1,
+)
 
 # reticolo Matlab
 ret_mat = pd.read_csv(base_path / "simulations" / "reticolo_matlab.csv")
@@ -57,7 +106,9 @@
 plt.figure(figsize=(10, 6))
 marker_size = 1
 linewidth = 1
-plt.plot(ret_energy, ret_eff, 'o-', label='grax', markersize=marker_size, linewidth=linewidth)
+for curve_label, curve_energy, curve_efficiency, curve_style in grax_curves:
+    plt.plot(curve_energy, curve_efficiency, marker='o', label=curve_label,
+             markersize=marker_size, linewidth=linewidth, **curve_style)
 plt.plot(ret_mat_energy, ret_mat_eff, 'd-', label='reticolo (Matlab)', markersize=marker_size, linewidth=linewidth)
 plt.plot(reflec_energy, reflec_eff, 's-', label='REFLEC', markersize=marker_size, linewidth=linewidth)
 plt.plot(diffmod_energy, diffmod_eff, '^-', label='DiffMod', markersize=marker_size, linewidth=linewidth)
diff --git a/validation/blazed/grating_definition.py b/validation/blazed/grating_definition.py
new file mode 100644
index 0000000..d3a4a70
--- /dev/null
+++ b/validation/blazed/grating_definition.py
@@ -0,0 +1,176 @@
+"""Grating and sweep definition for the blazed 600 l/mm validation case.
+
+Both `run_rcwa.py` and `run_neviere.py` import everything from here, so the two
+solver runs are guaranteed to see the same grating, the same energy grid and the
+same truncation. Anything defined per runner instead could drift between them,
+and the resulting comparison plot would show a "solver disagreement" that is
+really a mismatched sweep.
+
+Nothing in this module depends on which solver is used.
+"""
+
+from __future__ import annotations
+
+from functools import lru_cache
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+
+import grax
+
+CASE_ROOT = Path(__file__).resolve().parent
+OPTICAL_CONSTANTS_DIR = CASE_ROOT / "optical_constants"
+RESULTS_DIR = CASE_ROOT / "results"
+
+# Grating geometry.
+PERIOD_LPERMM = 600
+BLAZE_ANGLE_DEG = 0.729
+ANTI_BLAZE_ANGLE_DEG = 5.597
+LAYER_THICKNESS_NM = 30.0
+
+# Sweep settings shared by both solvers.
+CFF = 2.25
+POLARIZATION = "p"
+DIFFRACTION_ORDER = 1
+FOURIER_ORDERS = 20
+PLOT_ORDERS = [1, 2, 3]
+
+QUICK_ENERGIES_EV = np.asarray([100.0, 500.0, 1000.0], dtype=float)
+QUICK_FOURIER_ORDERS = 5
+
+
+@lru_cache(maxsize=None)
+def load_optical_constants(name: str) -> pd.DataFrame:
+    """Return one optical-constants table by material name.
+
+    Cached so repeated calls return the *same* object. ``MultilayerStack``
+    identifies ``top_material`` by matching it against ``material_a`` or
+    ``material_b``, which fails if each call hands back a fresh DataFrame.
+
+    Args:
+        name: Material name matching an ``OC_<name>_SSTR.dat`` file.
+
+    Returns:
+        Optical-constants table tagged with the material name.
+    """
+
+    table = pd.read_csv(
+        OPTICAL_CONSTANTS_DIR / f"OC_{name}_SSTR.dat",
+        sep=r"\s*,\s*|\s+",
+        engine="python",
+    )
+    table.attrs["name"] = name
+    return table
+
+
+def build_grating(*, quick: bool = False) -> grax.BlazedGrating:
+    """Return the blazed grating for this validation case.
+
+    Args:
+        quick: Use coarse resolutions for a fast smoke run.
+
+    Returns:
+        Configured blazed grating.
+    """
+
+    return grax.BlazedGrating(
+        period_lpermm=PERIOD_LPERMM,
+        blaze_angle_deg=BLAZE_ANGLE_DEG,
+        anti_blaze_angle_deg=ANTI_BLAZE_ANGLE_DEG,
+        substrate_material=load_optical_constants("Si"),
+        layer_material=load_optical_constants("Au"),
+        layer_thickness_nm=LAYER_THICKNESS_NM,
+        top_cap_material=None,
+        top_cap_thickness_nm=0.0,
+        z_resolution_nm=2.0 if quick else 0.1,
+        x_resolution_nm=10.0 if quick else 0.1,
+    )
+
+
+def build_energies_ev(*, quick: bool = False, stride: int = 1) -> np.ndarray:
+    """Return the photon energies swept by this case.
+
+    Args:
+        quick: Use the three-point smoke grid.
+        stride: Keep every Nth energy. Must be >= 1.
+
+    Returns:
+        Photon energies in electronvolts.
+    """
+
+    if stride < 1:
+        raise ValueError("stride must be >= 1.")
+    energies = QUICK_ENERGIES_EV if quick else np.arange(50.0, 2000.0, 10.0)
+    return energies[::stride]
+
+
+def build_cases(*, quick: bool = False, stride: int = 1):
+    """Return the batch cases for this sweep, identical for either solver.
+
+    Args:
+        quick: Use the coarse smoke configuration.
+        stride: Keep every Nth energy.
+
+    Returns:
+        Iterable of case dictionaries.
+    """
+
+    return grax.monochromator_cases(
+        grating=build_grating(quick=quick),
+        energies_ev=build_energies_ev(quick=quick, stride=stride),
+        period_lpermm=PERIOD_LPERMM,
+        diffraction_order=DIFFRACTION_ORDER,
+        cff=CFF,
+        polarization=POLARIZATION,
+    )
+
+
+def sweep_metadata(solver: str) -> dict[str, object]:
+    """Return checkpoint metadata describing this sweep.
+
+    Args:
+        solver: Solver used for the run.
+
+    Returns:
+        JSON-serializable metadata mapping.
+    """
+
+    return {
+        "grating_type": "BlazedGrating",
+        "period_lpermm": PERIOD_LPERMM,
+        "blaze_angle_deg": BLAZE_ANGLE_DEG,
+        "anti_blaze_angle_deg": ANTI_BLAZE_ANGLE_DEG,
+        "substrate_material": "Si",
+        "layer_material": "Au",
+        "layer_thickness_nm": LAYER_THICKNESS_NM,
+        "fourier_orders": FOURIER_ORDERS,
+        "cff": CFF,
+        "solver": solver,
+        "description": "Blazed grating monochromator sweep",
+    }
+
+
+def output_paths(solver: str) -> dict[str, Path]:
+    """Return the output paths for one solver's run.
+
+    The checked-in artifacts under ``results/`` keep their historical unsuffixed
+    names; every fresh run writes to a ``_rcwa`` or ``_neviere`` sibling.
+
+    Args:
+        solver: ``"rcwa"`` or ``"neviere"``.
+
+    Returns:
+        Mapping of output name to path.
+    """
+
+    if solver not in ("rcwa", "neviere"):
+        raise ValueError(f"solver must be 'rcwa' or 'neviere', got {solver!r}.")
+    RESULTS_DIR.mkdir(parents=True, exist_ok=True)
+    stem = "blazed_comparison_monochromator_orders_1_3"
+    return {
+        "all_orders_csv": RESULTS_DIR / f"{stem}_{solver}.csv",
+        "orders_plot": RESULTS_DIR / f"{stem}_{solver}.png",
+        "profile_plot": RESULTS_DIR / "blazed_comparison_profile.png",
+        "checkpoint_dir": RESULTS_DIR / f"checkpoints_{solver}",
+    }
diff --git a/validation/blazed/monochromator_sweep.py b/validation/blazed/monochromator_sweep.py
deleted file mode 100644
index cbabbfc..0000000
--- a/validation/blazed/monochromator_sweep.py
+++ /dev/null
@@ -1,107 +0,0 @@
-import numpy as np
-import pandas as pd
-
-from pathlib import Path
-import grax
-
-grax.setup_logging(level='INFO', run_id='blazed_sweep')
-
-
-example_root = Path(__file__).resolve().parent
-repo_root = Path(__file__).resolve().parents[2]
-optical_constants_dir = example_root / "optical_constants"
-results_dir = Path(__file__).resolve().parent / "results"
-results_dir.mkdir(parents=True, exist_ok=True)
-csv_path = results_dir / "blazed_comparison_monochromator_orders_1_3.csv"
-plot_path = results_dir / "blazed_comparison_monochromator_orders_1_3.png"
-profile_plot_path = results_dir / "blazed_comparison_profile.png"
-
-# Import Optical Constants
-silicon = pd.read_csv(
-    optical_constants_dir / "OC_Si_SSTR.dat",
-    # skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-silicon.attrs["name"] = "Si"
-gold = pd.read_csv(
-    optical_constants_dir / "OC_Au_SSTR.dat",
-    # skiprows=1,
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-gold.attrs["name"] = "Au"
-
-# Define Grating
-
-period_lpermm = 600
-blaze_angle_deg = 0.729
-anti_blaze_angle_deg = 5.597
-
-
-grating = grax.BlazedGrating(
-    period_lpermm=600,
-    blaze_angle_deg=0.729,
-    anti_blaze_angle_deg=5.597,
-    substrate_material=silicon,
-    layer_material=gold,
-    layer_thickness_nm=30.0,
-    top_cap_material=None,
-    top_cap_thickness_nm=0.0,
-    z_resolution_nm=0.1,
-    x_resolution_nm=0.1,
-)
-
-# Energy range
-energies_ev = np.arange(50.0, 2000.0, 10.0)
-
-# Use monochromator_cases helper
-cases = grax.monochromator_cases(
-    grating=grating,
-    energies_ev=energies_ev,
-    period_lpermm=period_lpermm,
-    diffraction_order=1,
-    cff=2.25,
-    polarization="p",
-)
-
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=20,
-    show_progress=True,
-    live_plot=True,
-    live_plot_x_key="energy_ev",
-    live_plot_order_count=3,
-    checkpoint_dir=results_dir / "checkpoints",
-    resume=False,  # Set to False to force restart from beginning
-    backend="numba",
-)
-
-grating.plot_profile(profile_plot_path)
-batch_result = list(runner.run_cases(
-    cases,
-    metadata={
-        "grating_type": "BlazedGrating",
-        "period_lpermm": period_lpermm,
-        "blaze_angle_deg": blaze_angle_deg,
-        "anti_blaze_angle_deg": anti_blaze_angle_deg,
-        "substrate_material": "Si",
-        "layer_material": "Au",
-        "layer_thickness_nm": 30.0,
-        "fourier_orders": 20,
-        "backend": "numba",
-        "description": "Blazed grating monochromator sweep",
-    }
-))
-grax.write_all_orders_csv(batch_result, csv_path)
-grax.plot_order_subset(
-    batch_result,
-    plot_path,
-    diffraction_orders=[1, 2, 3],
-    title="Blazed Grating Monochromator Sweep (600 l/mm, BA=0.729 deg): Orders 1-3",
-)
-
-print(f"Computed {sum(case.status == 'ok' for case in batch_result)} monochromator points.")
-print(f"Profile plot saved to: {profile_plot_path}")
-print(f"Monochromator sweep CSV saved to: {csv_path}")
-print(f"Monochromator orders plot saved to: {plot_path}")
diff --git a/validation/blazed/parameter_influence_study.py b/validation/blazed/parameter_influence_study.py
index f1d380e..7edc171 100644
--- a/validation/blazed/parameter_influence_study.py
+++ b/validation/blazed/parameter_influence_study.py
@@ -80,8 +80,8 @@
 sweeps_dir.mkdir(parents=True, exist_ok=True)
 all_rows = []
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=15,
+    diffraction_order=1,
+    fourier_orders=15,
     show_progress=True,
     on_error="continue",
     resume=False,
diff --git a/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_neviere.csv b/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_neviere.csv
new file mode 100644
index 0000000..1a823c1
--- /dev/null
+++ b/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_neviere.csv
@@ -0,0 +1,7996 @@
+case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
+mono-00000000,50.0,4.882210444916382,-20,6.934670436812611e-08,45.667609571763236
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diff --git a/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_neviere.png b/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_neviere.png
new file mode 100644
index 0000000..d23d527
Binary files /dev/null and b/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_neviere.png differ
diff --git a/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_rcwa.csv b/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_rcwa.csv
new file mode 100644
index 0000000..bded509
--- /dev/null
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diff --git a/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_rcwa.png b/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_rcwa.png
new file mode 100644
index 0000000..180715c
Binary files /dev/null and b/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_rcwa.png differ
diff --git a/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_solver_comparison.csv b/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_solver_comparison.csv
new file mode 100644
index 0000000..f8fef98
--- /dev/null
+++ b/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_solver_comparison.csv
@@ -0,0 +1,4 @@
+order,shared_points,max_abs_deviation,mean_abs_deviation,rms_deviation,peak_rcwa_efficiency,max_deviation_over_peak
+1,195,4.2431058666636545e-12,1.1662917426696469e-12,1.6409938703312865e-12,0.253901752327676,1.671160528733832e-11
+2,195,2.206901328349886e-12,6.745878293679457e-13,9.52178831546566e-13,0.1375191888068723,1.6047951907636615e-11
+3,195,2.346400851394037e-12,8.407013894218514e-13,1.211720461253796e-12,0.0288587852586866,8.130629305291919e-11
diff --git a/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_solver_comparison.png b/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_solver_comparison.png
new file mode 100644
index 0000000..bcb7449
Binary files /dev/null and b/validation/blazed/results/blazed_comparison_monochromator_orders_1_3_solver_comparison.png differ
diff --git a/validation/blazed/run_neviere.py b/validation/blazed/run_neviere.py
new file mode 100644
index 0000000..255e97b
--- /dev/null
+++ b/validation/blazed/run_neviere.py
@@ -0,0 +1,86 @@
+"""Run the blazed 600 l/mm monochromator sweep with the Nevière differential method.
+
+Writes ``results/blazed_comparison_monochromator_orders_1_3_neviere.csv`` plus an
+orders 1-3 plot. The grating and the sweep grid come from
+``grating_definition.py``, which ``run_rcwa.py`` also uses, so the two runs
+stay comparable.
+
+```bash
+python validation/blazed/run_neviere.py
+python validation/blazed/run_neviere.py --quick
+```
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+parser = argparse.ArgumentParser(description="Blazed 600 l/mm monochromator sweep (Nevière)")
+parser.add_argument("--quick", action="store_true", help="Run a few coarse energy points")
+parser.add_argument("--stride", type=int, default=1, help="Keep every Nth energy point")
+parser.add_argument("--live-plot", action="store_true", help="Show the sweep while it runs")
+args = parser.parse_args()
+
+os.environ.setdefault("MPLBACKEND", "TkAgg" if args.live_plot else "Agg")
+
+import grax  # noqa: E402
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+import grating_definition as case  # noqa: E402
+
+SOLVER = "neviere"
+SOLVER_TITLE = "Nevière DM"
+
+
+def main() -> None:
+    """Run the sweep and write this solver's artifacts."""
+
+    grax.setup_logging(level="INFO", run_id=f"blazed_sweep_{SOLVER}")
+    paths = case.output_paths(SOLVER)
+
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=case.DIFFRACTION_ORDER,
+        fourier_orders=case.QUICK_FOURIER_ORDERS if args.quick else case.FOURIER_ORDERS,
+        show_progress=True,
+        live_plot=args.live_plot,
+        live_plot_x_key="energy_ev",
+        live_plot_order_count=3,
+        checkpoint_dir=paths["checkpoint_dir"],
+        resume=False,
+        backend="numba",
+        solver=SOLVER,
+    )
+
+    case.build_grating(quick=args.quick).plot_profile(paths["profile_plot"])
+    results = list(
+        runner.run_cases(
+            case.build_cases(quick=args.quick, stride=args.stride),
+            metadata=case.sweep_metadata(SOLVER),
+        )
+    )
+
+    grax.write_all_orders_csv(results, paths["all_orders_csv"])
+    grax.plot_order_subset(
+        results,
+        paths["orders_plot"],
+        diffraction_orders=case.PLOT_ORDERS,
+        title=(
+            f"Blazed Grating Monochromator Sweep ({case.PERIOD_LPERMM} l/mm, "
+            f"BA={case.BLAZE_ANGLE_DEG} deg), {SOLVER_TITLE}: Orders 1-3"
+        ),
+    )
+
+    successful = sum(result.status == "ok" for result in results)
+    print(f"Computed {successful} monochromator points with the {SOLVER} solver.")
+    print(f"All-orders CSV saved to: {paths['all_orders_csv']}")
+    print(f"Orders plot saved to: {paths['orders_plot']}")
+    print(f"Grating profile saved to: {paths['profile_plot']}")
+
+
+# Spawned multiprocessing workers re-import this file by path; without the guard
+# each worker would re-run the whole sweep and recursively spawn more.
+if __name__ == "__main__":
+    main()
diff --git a/validation/blazed/run_rcwa.py b/validation/blazed/run_rcwa.py
new file mode 100644
index 0000000..203e718
--- /dev/null
+++ b/validation/blazed/run_rcwa.py
@@ -0,0 +1,86 @@
+"""Run the blazed 600 l/mm monochromator sweep with the RCWA solver.
+
+Writes ``results/blazed_comparison_monochromator_orders_1_3_rcwa.csv`` plus an
+orders 1-3 plot. The grating and the sweep grid come from
+``grating_definition.py``, which ``run_neviere.py`` also uses, so the two runs
+stay comparable.
+
+```bash
+python validation/blazed/run_rcwa.py
+python validation/blazed/run_rcwa.py --quick
+```
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+parser = argparse.ArgumentParser(description="Blazed 600 l/mm monochromator sweep (RCWA)")
+parser.add_argument("--quick", action="store_true", help="Run a few coarse energy points")
+parser.add_argument("--stride", type=int, default=1, help="Keep every Nth energy point")
+parser.add_argument("--live-plot", action="store_true", help="Show the sweep while it runs")
+args = parser.parse_args()
+
+os.environ.setdefault("MPLBACKEND", "TkAgg" if args.live_plot else "Agg")
+
+import grax  # noqa: E402
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+import grating_definition as case  # noqa: E402
+
+SOLVER = "rcwa"
+SOLVER_TITLE = "RCWA"
+
+
+def main() -> None:
+    """Run the sweep and write this solver's artifacts."""
+
+    grax.setup_logging(level="INFO", run_id=f"blazed_sweep_{SOLVER}")
+    paths = case.output_paths(SOLVER)
+
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=case.DIFFRACTION_ORDER,
+        fourier_orders=case.QUICK_FOURIER_ORDERS if args.quick else case.FOURIER_ORDERS,
+        show_progress=True,
+        live_plot=args.live_plot,
+        live_plot_x_key="energy_ev",
+        live_plot_order_count=3,
+        checkpoint_dir=paths["checkpoint_dir"],
+        resume=False,
+        backend="numba",
+        solver=SOLVER,
+    )
+
+    case.build_grating(quick=args.quick).plot_profile(paths["profile_plot"])
+    results = list(
+        runner.run_cases(
+            case.build_cases(quick=args.quick, stride=args.stride),
+            metadata=case.sweep_metadata(SOLVER),
+        )
+    )
+
+    grax.write_all_orders_csv(results, paths["all_orders_csv"])
+    grax.plot_order_subset(
+        results,
+        paths["orders_plot"],
+        diffraction_orders=case.PLOT_ORDERS,
+        title=(
+            f"Blazed Grating Monochromator Sweep ({case.PERIOD_LPERMM} l/mm, "
+            f"BA={case.BLAZE_ANGLE_DEG} deg), {SOLVER_TITLE}: Orders 1-3"
+        ),
+    )
+
+    successful = sum(result.status == "ok" for result in results)
+    print(f"Computed {successful} monochromator points with the {SOLVER} solver.")
+    print(f"All-orders CSV saved to: {paths['all_orders_csv']}")
+    print(f"Orders plot saved to: {paths['orders_plot']}")
+    print(f"Grating profile saved to: {paths['profile_plot']}")
+
+
+# Spawned multiprocessing workers re-import this file by path; without the guard
+# each worker would re-run the whole sweep and recursively spawn more.
+if __name__ == "__main__":
+    main()
diff --git a/validation/blazed_multilayer/blazed_multilayer_sweep.py b/validation/blazed_multilayer/blazed_multilayer_sweep.py
deleted file mode 100644
index 209429e..0000000
--- a/validation/blazed_multilayer/blazed_multilayer_sweep.py
+++ /dev/null
@@ -1,157 +0,0 @@
-"""Blazed multilayer energy-angle sweep matched to DiffraMod input pairs."""
-
-from __future__ import annotations
-
-import argparse
-from pathlib import Path
-
-import matplotlib.pyplot as plt
-import numpy as np
-import pandas as pd
-
-import grax
-
-grax.setup_logging(level="INFO", run_id="blazed_multilayer_sweep")
-
-parser = argparse.ArgumentParser(description="Blazed multilayer energy-angle sweep")
-parser.add_argument(
-    "--quick",
-    action="store_true",
-    help="Run with fewer energy-angle points for quick testing",
-)
-args = parser.parse_args()
-
-example_root = Path(__file__).resolve().parent
-optical_constants_dir = example_root / "optical_constants"
-simulation_dir = example_root / "simulation"
-output_dir = example_root / "results"
-output_dir.mkdir(parents=True, exist_ok=True)
-
-silicon = pd.read_csv(
-    optical_constants_dir / "OC_Si_SSTR.dat",
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-silicon.attrs["name"] = "Si"
-chromium = pd.read_csv(
-    optical_constants_dir / "OC_Cr_SSTR.dat",
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-chromium.attrs["name"] = "Cr"
-carbon = pd.read_csv(
-    optical_constants_dir / "OC_C_SSTR.dat",
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-carbon.attrs["name"] = "C"
-
-reference_data = pd.read_csv(
-    simulation_dir / "DiffractMod_CrC_d4.8_N60.dat",
-    sep=r"\s+",
-    engine="python",
-)
-reference_data = reference_data[["Energy", "Efficiency(GR)", "alpha"]].copy()
-reference_data = reference_data.apply(pd.to_numeric, errors="coerce").dropna()
-reference_data = reference_data.reset_index(drop=True)
-
-if args.quick:
-    sampled_reference = reference_data.iloc[::100].copy()
-    x_resolution_nm = 1
-    z_resolution_nm = 1
-    default_fourier_orders = 10
-else:
-    sampled_reference = reference_data.iloc[::1].copy()
-    x_resolution_nm = 0.1
-    z_resolution_nm = 0.01
-    default_fourier_orders = 35
-
-energy_angle_pairs = list(
-    zip(
-        sampled_reference["Energy"].to_numpy(dtype=float),
-        sampled_reference["alpha"].to_numpy(dtype=float),
-    )
-)
-
-multilayer_stack = grax.MultilayerStack(
-    substrate_material=silicon,
-    material_a=chromium,
-    material_b=carbon,
-    d_period_nm=4.8,
-    gamma=0.4,
-    n_bilayers=60,
-    top_material=carbon,
-)
-
-grating = grax.BlazedGrating(
-    period_lpermm=2400,
-    blaze_angle_deg=1.37,
-    anti_blaze_angle_deg=3.25,
-    coating_stack=multilayer_stack,
-    x_resolution_nm=x_resolution_nm,
-    z_resolution_nm=z_resolution_nm,
-)
-
-cases = grax.energy_angle_cases(
-    grating=grating,
-    energy_angle_pairs=energy_angle_pairs,
-    polarization="p",
-)
-
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=2,
-    default_fourier_orders=default_fourier_orders,
-    show_progress=True,
-    live_plot=True,
-    live_plot_x_key="energy_ev",
-    live_plot_order_count=2,
-    live_plot_reference_data=sampled_reference[["Energy", "Efficiency(GR)"]].to_numpy(dtype=float),
-    on_error="fail_fast",
-    max_workers='auto',
-    checkpoint_dir=output_dir / "checkpoints",
-    resume=False,
-    backend="numba",
-)
-
-csv_path = output_dir / "blazed_multilayer_all_orders.csv"
-profile_plot_path = output_dir / "blazed_multilayer_profile.png"
-stack_plot_path = output_dir / "multilayer_stack_schematic.png"
-selected_order_plot_path = output_dir / "blazed_multilayer_order_2.png"
-
-results = list(runner.run_cases(cases))
-grax.write_all_orders_csv(results, csv_path)
-grating.plot_profile(profile_plot_path)
-multilayer_stack.plot_schematic(stack_plot_path)
-
-successful_results = [result for result in results if result.status == "ok"]
-figure, axis = plt.subplots(figsize=(10, 6))
-axis.plot(
-    [result.energy_ev for result in successful_results],
-    [result.selected_efficiency for result in successful_results],
-    "o-",
-    linewidth=1.0,
-    markersize=2.0,
-    label="grax",
-)
-axis.plot(
-    sampled_reference["Energy"],
-    sampled_reference["Efficiency(GR)"],
-    "s-",
-    linewidth=1.0,
-    markersize=2.0,
-    label="DiffraMod",
-)
-axis.set_xlabel("Energy (eV)")
-axis.set_ylabel("Efficiency (2nd order)")
-axis.set_title("Blazed Multilayer Energy-Angle Sweep: 2nd Order")
-axis.grid(True, alpha=0.3)
-axis.legend(loc="best")
-figure.tight_layout()
-figure.savefig(selected_order_plot_path, dpi=150, bbox_inches="tight")
-plt.close(figure)
-
-print(f"Computed {len(successful_results)} energy-angle points.")
-print(f"Results saved to: {csv_path}")
-print(f"Selected-order plot saved to: {selected_order_plot_path}")
-print(f"Profile plot saved to: {profile_plot_path}")
-print(f"Stack schematic saved to: {stack_plot_path}")
diff --git a/validation/blazed_multilayer/comparison_blazed_multilayer_grating_angle.png b/validation/blazed_multilayer/comparison_blazed_multilayer_grating_angle.png
index b715f8e..bf85252 100644
Binary files a/validation/blazed_multilayer/comparison_blazed_multilayer_grating_angle.png and b/validation/blazed_multilayer/comparison_blazed_multilayer_grating_angle.png differ
diff --git a/validation/blazed_multilayer/comparison_blazed_multilayer_sweep.png b/validation/blazed_multilayer/comparison_blazed_multilayer_sweep.png
index 56844f6..5f36849 100644
Binary files a/validation/blazed_multilayer/comparison_blazed_multilayer_sweep.png and b/validation/blazed_multilayer/comparison_blazed_multilayer_sweep.png differ
diff --git a/validation/blazed_multilayer/comparison_blazed_multilayer_sweep.py b/validation/blazed_multilayer/comparison_blazed_multilayer_sweep.py
index 369cfb7..c9956e9 100644
--- a/validation/blazed_multilayer/comparison_blazed_multilayer_sweep.py
+++ b/validation/blazed_multilayer/comparison_blazed_multilayer_sweep.py
@@ -8,14 +8,64 @@
 import pandas as pd
 
 
+# Both solvers' results are plotted when present. A fresh run writes
+# ``*_rcwa.csv`` / ``*_neviere.csv``; the unsuffixed CSV is the older checked-in
+# artifact and is only used as a fallback, because it predates several solver
+# changes and pairing it against a fresh run would show that drift as though it
+# were a difference between the two methods.
+SOLVER_LABELS = {"rcwa": "graxpy (RCWA)", "neviere": "graxpy (Nevière DM)"}
+# The two solvers agree to ~1e-11, so without a dashed overlay the second curve
+# hides the first completely and the plot looks as though one is missing.
+SOLVER_STYLES = {"rcwa": {"linestyle": "-"}, "neviere": {"linestyle": (0, (6, 4))}}
+
+
+def load_solver_curves(base_csv, order):
+    """Return (label, energy, efficiency, style) for each solver that has been run.
+
+    Args:
+        base_csv: Historical unsuffixed all-orders CSV path for this case.
+        order: Signed diffraction order to extract (reflected orders are negative).
+
+    Returns:
+        List of plottable curves, skipping solvers with no results yet.
+    """
+
+    curves = []
+    for solver in ("rcwa", "neviere"):
+        candidates = [base_csv.with_name(f"{base_csv.stem}_{solver}{base_csv.suffix}")]
+        if solver == "rcwa":
+            candidates.append(base_csv)
+        path = next((candidate for candidate in candidates if candidate.exists()), None)
+        if path is None:
+            print(f"  note: no {solver} results yet, skipping that curve")
+            continue
+        frame = pd.read_csv(path)
+        selected = frame[frame["order"] == order].sort_values("energy_ev")
+        if selected.empty:
+            print(f"  note: {path.name} has no order {order}, skipping that curve")
+            continue
+        print(f"  {SOLVER_LABELS[solver]:<22} <- {path.name}  ({len(selected)} points)")
+        curves.append(
+            (
+                SOLVER_LABELS[solver],
+                selected["energy_ev"],
+                selected["efficiency"],
+                dict(SOLVER_STYLES[solver]),
+            )
+        )
+    return curves
+
+
 
 base_path = Path(__file__).resolve().parent
 project_root = base_path.parent.parent
 theta_search_results_path = project_root / "examples" / "simulation" / "multilayer_theta_search" / "results"
 
-grax_results = pd.read_csv(base_path / "results" / "blazed_multilayer_all_orders.csv")
-grax_order = grax_results[grax_results["order"] == -2].copy()
-grax_order = grax_order.sort_values("energy_ev")
+print("graxpy curves:")
+grax_curves = load_solver_curves(
+    base_path / "results" / "blazed_multilayer_all_orders.csv",
+    order=-2,
+)
 
 theta_search_results = pd.read_csv(
     theta_search_results_path / "multilayer_theta_search_all_orders.csv"
@@ -32,13 +82,16 @@
 diffmod_results = diffmod_results.apply(pd.to_numeric, errors="coerce").dropna()
 
 plt.figure(figsize=(10, 6))
-plt.plot(
-    grax_order["energy_ev"],
-    grax_order["efficiency"],
-    label="grax energy-angle",
-    linewidth=1.0,
-    linestyle=":",
-)
+for curve_label, curve_energy, curve_efficiency, curve_style in grax_curves:
+    plt.plot(
+        curve_energy,
+        curve_efficiency,
+        label=f"{curve_label} energy-angle",
+        linewidth=1.0,
+        marker=".",
+        markersize=3,
+        **curve_style,
+    )
 plt.plot(
     theta_search_order["energy_ev"],
     theta_search_order["efficiency"],
@@ -67,13 +120,16 @@
 print(f"Plot saved to: {output_path}")
 
 plt.figure(figsize=(10, 6))
-plt.plot(
-    grax_order["energy_ev"],
-    grax_order["efficiency"],
-    label="grax energy-angle",
-    linewidth=1.0,
-    linestyle="-",
-)
+for curve_label, curve_energy, curve_efficiency, curve_style in grax_curves:
+    plt.plot(
+        curve_energy,
+        curve_efficiency,
+        label=f"{curve_label} energy-angle",
+        linewidth=1.0,
+        marker=".",
+        markersize=4,
+        **curve_style,
+    )
 plt.plot(
     theta_search_order["energy_ev"],
     theta_search_order["efficiency"],
diff --git a/validation/blazed_multilayer/comparison_blazed_multilayer_sweep_550_600eV.png b/validation/blazed_multilayer/comparison_blazed_multilayer_sweep_550_600eV.png
index 6811173..9151a64 100644
Binary files a/validation/blazed_multilayer/comparison_blazed_multilayer_sweep_550_600eV.png and b/validation/blazed_multilayer/comparison_blazed_multilayer_sweep_550_600eV.png differ
diff --git a/validation/blazed_multilayer/grating_definition.py b/validation/blazed_multilayer/grating_definition.py
new file mode 100644
index 0000000..bb326a3
--- /dev/null
+++ b/validation/blazed_multilayer/grating_definition.py
@@ -0,0 +1,192 @@
+"""Grating and sweep definition for the blazed 2400 l/mm multilayer case.
+
+Both `run_rcwa.py` and `run_neviere.py` import everything from here, so the two
+solver runs are guaranteed to see the same grating, the same energy-angle grid
+and the same truncation. Anything defined per runner instead could drift between
+them, and the resulting comparison plot would show a "solver disagreement" that
+is really a mismatched sweep.
+
+The sweep grid is not a plain energy range: each point is an (energy, grazing
+angle) pair taken from the DiffractMod reference table, so grax is evaluated at
+exactly the geometry the reference code used.
+
+Nothing in this module depends on which solver is used.
+"""
+
+from __future__ import annotations
+
+from functools import lru_cache
+from pathlib import Path
+
+import pandas as pd
+
+import grax
+
+CASE_ROOT = Path(__file__).resolve().parent
+OPTICAL_CONSTANTS_DIR = CASE_ROOT / "optical_constants"
+SIMULATION_DIR = CASE_ROOT / "simulation"
+RESULTS_DIR = CASE_ROOT / "results"
+REFERENCE_FILE = SIMULATION_DIR / "DiffractMod_CrC_d4.8_N60.dat"
+
+# Grating and multilayer geometry.
+PERIOD_LPERMM = 2400
+BLAZE_ANGLE_DEG = 1.37
+ANTI_BLAZE_ANGLE_DEG = 3.25
+BILAYER_PERIOD_NM = 4.8
+GAMMA = 0.4
+N_BILAYERS = 60
+
+# Sweep settings shared by both solvers.
+POLARIZATION = "p"
+DIFFRACTION_ORDER = 2
+FOURIER_ORDERS = 35
+X_RESOLUTION_NM = 0.1
+Z_RESOLUTION_NM = 0.01
+
+QUICK_FOURIER_ORDERS = 10
+QUICK_X_RESOLUTION_NM = 1.0
+QUICK_Z_RESOLUTION_NM = 1.0
+# A quick run walks the reference table in coarse jumps instead of every row.
+QUICK_REFERENCE_STEP = 100
+
+
+@lru_cache(maxsize=None)
+def load_optical_constants(name: str) -> pd.DataFrame:
+    """Return one optical-constants table by material name.
+
+    Cached so repeated calls return the *same* object. ``MultilayerStack``
+    identifies ``top_material`` by matching it against ``material_a`` or
+    ``material_b``, which fails if each call hands back a fresh DataFrame.
+
+    Args:
+        name: Material name matching an ``OC_<name>_SSTR.dat`` file.
+
+    Returns:
+        Optical-constants table tagged with the material name.
+    """
+
+    table = pd.read_csv(
+        OPTICAL_CONSTANTS_DIR / f"OC_{name}_SSTR.dat",
+        sep=r"\s*,\s*|\s+",
+        engine="python",
+    )
+    table.attrs["name"] = name
+    return table
+
+
+def load_reference_table() -> pd.DataFrame:
+    """Return the DiffractMod reference table driving the sweep grid.
+
+    Returns:
+        Energy, efficiency and grazing angle columns, numeric and NaN-free.
+    """
+
+    table = pd.read_csv(REFERENCE_FILE, sep=r"\s+", engine="python")
+    table = table[["Energy", "Efficiency(GR)", "alpha"]].copy()
+    table = table.apply(pd.to_numeric, errors="coerce").dropna()
+    return table.reset_index(drop=True)
+
+
+def build_reference_grid(*, quick: bool = False, stride: int = 1) -> pd.DataFrame:
+    """Return the subsampled reference rows this sweep evaluates.
+
+    Args:
+        quick: Take coarse jumps through the reference table.
+        stride: Keep every Nth reference row. Must be >= 1.
+
+    Returns:
+        Subsampled reference table.
+    """
+
+    if stride < 1:
+        raise ValueError("stride must be >= 1.")
+    step = (QUICK_REFERENCE_STEP * stride) if quick else stride
+    return load_reference_table().iloc[::step].copy()
+
+
+def build_grating(*, quick: bool = False) -> grax.BlazedGrating:
+    """Return the blazed grating on its Cr/C multilayer stack.
+
+    Args:
+        quick: Use coarse resolutions for a fast smoke run.
+
+    Returns:
+        Configured blazed grating.
+    """
+
+    return grax.BlazedGrating(
+        period_lpermm=PERIOD_LPERMM,
+        blaze_angle_deg=BLAZE_ANGLE_DEG,
+        anti_blaze_angle_deg=ANTI_BLAZE_ANGLE_DEG,
+        coating_stack=build_multilayer_stack(),
+        x_resolution_nm=QUICK_X_RESOLUTION_NM if quick else X_RESOLUTION_NM,
+        z_resolution_nm=QUICK_Z_RESOLUTION_NM if quick else Z_RESOLUTION_NM,
+    )
+
+
+def build_multilayer_stack() -> grax.MultilayerStack:
+    """Return the Cr/C multilayer stack under the grating profile.
+
+    Returns:
+        Configured multilayer stack.
+    """
+
+    return grax.MultilayerStack(
+        substrate_material=load_optical_constants("Si"),
+        material_a=load_optical_constants("Cr"),
+        material_b=load_optical_constants("C"),
+        d_period_nm=BILAYER_PERIOD_NM,
+        gamma=GAMMA,
+        n_bilayers=N_BILAYERS,
+        top_material=load_optical_constants("C"),
+    )
+
+
+def build_cases(*, quick: bool = False, stride: int = 1):
+    """Return the batch cases for this sweep, identical for either solver.
+
+    Args:
+        quick: Use the coarse smoke configuration.
+        stride: Keep every Nth reference row.
+
+    Returns:
+        Iterable of case dictionaries.
+    """
+
+    reference = build_reference_grid(quick=quick, stride=stride)
+    energy_angle_pairs = list(
+        zip(
+            reference["Energy"].to_numpy(dtype=float),
+            reference["alpha"].to_numpy(dtype=float),
+        )
+    )
+    return grax.energy_angle_cases(
+        grating=build_grating(quick=quick),
+        energy_angle_pairs=energy_angle_pairs,
+        polarization=POLARIZATION,
+    )
+
+
+def output_paths(solver: str) -> dict[str, Path]:
+    """Return the output paths for one solver's run.
+
+    The checked-in artifacts under ``results/`` keep their historical unsuffixed
+    names; every fresh run writes to a ``_rcwa`` or ``_neviere`` sibling.
+
+    Args:
+        solver: ``"rcwa"`` or ``"neviere"``.
+
+    Returns:
+        Mapping of output name to path.
+    """
+
+    if solver not in ("rcwa", "neviere"):
+        raise ValueError(f"solver must be 'rcwa' or 'neviere', got {solver!r}.")
+    RESULTS_DIR.mkdir(parents=True, exist_ok=True)
+    return {
+        "all_orders_csv": RESULTS_DIR / f"blazed_multilayer_all_orders_{solver}.csv",
+        "selected_order_plot": RESULTS_DIR / f"blazed_multilayer_order_2_{solver}.png",
+        "profile_plot": RESULTS_DIR / "blazed_multilayer_profile.png",
+        "stack_plot": RESULTS_DIR / "multilayer_stack_schematic.png",
+        "checkpoint_dir": RESULTS_DIR / f"checkpoints_{solver}",
+    }
diff --git a/validation/blazed_multilayer/parameter_influence_study.py b/validation/blazed_multilayer/parameter_influence_study.py
index 5563cb2..7007eaa 100644
--- a/validation/blazed_multilayer/parameter_influence_study.py
+++ b/validation/blazed_multilayer/parameter_influence_study.py
@@ -76,8 +76,8 @@
 )
 
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=2,
-    default_fourier_orders=15,
+    diffraction_order=2,
+    fourier_orders=15,
     show_progress=True,
     on_error="continue",
     resume=False,
diff --git a/validation/blazed_multilayer/results/blazed_multilayer_all_orders_neviere.csv b/validation/blazed_multilayer/results/blazed_multilayer_all_orders_neviere.csv
new file mode 100644
index 0000000..ede0c58
--- /dev/null
+++ b/validation/blazed_multilayer/results/blazed_multilayer_all_orders_neviere.csv
@@ -0,0 +1,12284 @@
+case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
+pair-00000000,500.0,14.17636,-35,5.2249404359906484e-11,40.42458994898186
+pair-00000000,500.0,14.17636,-34,4.110339019096922e-11,39.89589382220741
+pair-00000000,500.0,14.17636,-33,2.439847472936944e-11,39.36129647021034
+pair-00000000,500.0,14.17636,-32,3.511425605572851e-11,38.82054759357165
+pair-00000000,500.0,14.17636,-31,1.369433904087022e-10,38.27337991663385
+pair-00000000,500.0,14.17636,-30,7.521223242055397e-11,37.719507524000484
+pair-00000000,500.0,14.17636,-29,3.391543804299928e-11,37.158623981880474
+pair-00000000,500.0,14.17636,-28,3.2680259736532366e-10,36.5904002092737
+pair-00000000,500.0,14.17636,-27,1.7951096894524718e-10,36.014482057061635
+pair-00000000,500.0,14.17636,-26,3.292145529434414e-11,35.430487544498185
+pair-00000000,500.0,14.17636,-25,3.734849648804147e-10,34.83800369194473
+pair-00000000,500.0,14.17636,-24,3.174095311275941e-10,34.236582875360064
+pair-00000000,500.0,14.17636,-23,1.1036450838600642e-10,33.625738611255784
+pair-00000000,500.0,14.17636,-22,1.9323509319847775e-10,33.00494065949575
+pair-00000000,500.0,14.17636,-21,9.36601869710676e-10,32.373609304022494
+pair-00000000,500.0,14.17636,-20,6.747781973691452e-10,31.73110863636711
+pair-00000000,500.0,14.17636,-19,1.51677283371191e-10,31.076738620929298
+pair-00000000,500.0,14.17636,-18,2.5398953828967513e-09,30.40972566069736
+pair-00000000,500.0,14.17636,-17,1.611370328828262e-09,29.729211301938086
+pair-00000000,500.0,14.17636,-16,4.896366492437184e-10,29.03423860869232
+pair-00000000,500.0,14.17636,-15,3.973663738658616e-09,28.323735591416423
+pair-00000000,500.0,14.17636,-14,2.369919763818012e-09,27.5964948721599
+pair-00000000,500.0,14.17636,-13,2.9452108806813555e-09,26.851148486209645
+pair-00000000,500.0,14.17636,-12,4.180571750172392e-09,26.08613631872735
+pair-00000000,500.0,14.17636,-11,1.10681367222073e-08,25.29966609440254
+pair-00000000,500.0,14.17636,-10,1.439521483039112e-08,24.489661982199763
+pair-00000000,500.0,14.17636,-9,1.438777779919389e-08,23.653697587709246
+pair-00000000,500.0,14.17636,-8,7.416485153815925e-08,22.788907115258382
+pair-00000000,500.0,14.17636,-7,2.7848576917531245e-08,21.89186532520057
+pair-00000000,500.0,14.17636,-6,3.593888823306422e-07,20.958421747667003
+pair-00000000,500.0,14.17636,-5,7.241880330219837e-07,19.98346586030081
+pair-00000000,500.0,14.17636,-4,1.7522980634431596e-06,18.960584473633418
+pair-00000000,500.0,14.17636,-3,0.00012123090547031899,17.88154389115782
+pair-00000000,500.0,14.17636,-2,0.006842660486413587,16.735473054396437
+pair-00000000,500.0,14.17636,-1,5.271029483419842e-05,15.507505003914389
+pair-00000000,500.0,14.17636,0,1.4091950174153748e-05,14.176360000000017
+pair-00000000,500.0,14.17636,1,7.185946158106956e-07,12.709645440376349
+pair-00000000,500.0,14.17636,2,2.0465468900868174e-05,11.053508139757653
+pair-00000000,500.0,14.17636,3,5.59379270783269e-05,9.105145158871807
+pair-00000000,500.0,14.17636,4,5.5696925394347444e-05,6.61102028673325
+pair-00000000,500.0,14.17636,5,1.8253654577905876e-05,2.141361994584713
+pair-00000000,500.0,14.17636,6,0.0,0.0
+pair-00000000,500.0,14.17636,7,0.0,0.0
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diff --git a/validation/blazed_multilayer/results/blazed_multilayer_all_orders_rcwa.csv b/validation/blazed_multilayer/results/blazed_multilayer_all_orders_rcwa.csv
new file mode 100644
index 0000000..12bf1df
--- /dev/null
+++ b/validation/blazed_multilayer/results/blazed_multilayer_all_orders_rcwa.csv
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diff --git a/validation/blazed_multilayer/results/blazed_multilayer_all_orders_solver_comparison.csv b/validation/blazed_multilayer/results/blazed_multilayer_all_orders_solver_comparison.csv
new file mode 100644
index 0000000..f4293b6
--- /dev/null
+++ b/validation/blazed_multilayer/results/blazed_multilayer_all_orders_solver_comparison.csv
@@ -0,0 +1,4 @@
+order,shared_points,max_abs_deviation,mean_abs_deviation,rms_deviation,peak_rcwa_efficiency,max_deviation_over_peak
+1,173,2.275500100845651e-12,3.2557182436915704e-13,4.468409665359072e-13,0.0071222216549632,3.194930193249382e-10
+2,173,8.666301010151756e-11,9.09151492624247e-12,1.809458261831316e-11,0.6750296855275403,1.283839984515493e-10
+3,173,1.1885999996741337e-12,1.7049279259914336e-13,2.620457564146426e-13,0.0020495738209983,5.799254398630024e-10
diff --git a/validation/blazed_multilayer/results/blazed_multilayer_all_orders_solver_comparison.png b/validation/blazed_multilayer/results/blazed_multilayer_all_orders_solver_comparison.png
new file mode 100644
index 0000000..e730ed0
Binary files /dev/null and b/validation/blazed_multilayer/results/blazed_multilayer_all_orders_solver_comparison.png differ
diff --git a/validation/blazed_multilayer/results/blazed_multilayer_order_2_neviere.png b/validation/blazed_multilayer/results/blazed_multilayer_order_2_neviere.png
new file mode 100644
index 0000000..3a42a2b
Binary files /dev/null and b/validation/blazed_multilayer/results/blazed_multilayer_order_2_neviere.png differ
diff --git a/validation/blazed_multilayer/results/blazed_multilayer_order_2_rcwa.png b/validation/blazed_multilayer/results/blazed_multilayer_order_2_rcwa.png
new file mode 100644
index 0000000..9fdcae0
Binary files /dev/null and b/validation/blazed_multilayer/results/blazed_multilayer_order_2_rcwa.png differ
diff --git a/validation/blazed_multilayer/run_neviere.py b/validation/blazed_multilayer/run_neviere.py
new file mode 100644
index 0000000..df63a13
--- /dev/null
+++ b/validation/blazed_multilayer/run_neviere.py
@@ -0,0 +1,109 @@
+"""Run the blazed 2400 l/mm multilayer energy-angle sweep with the Nevière differential method.
+
+Writes ``results/blazed_multilayer_all_orders_neviere.csv`` plus a second-order plot
+against the DiffractMod reference. The grating and the sweep grid come from
+``grating_definition.py``, which ``run_rcwa.py`` also uses, so the two runs
+stay comparable.
+
+This is the most expensive validation case: at full resolution each point solves
+a 60-bilayer stack sliced at 0.01 nm. Use ``--stride`` to subsample the 1727
+reference points.
+
+```bash
+python validation/blazed_multilayer/run_neviere.py --stride 10
+python validation/blazed_multilayer/run_neviere.py --quick
+```
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+parser = argparse.ArgumentParser(description="Blazed multilayer energy-angle sweep (Nevière)")
+parser.add_argument("--quick", action="store_true", help="Run a few coarse points")
+parser.add_argument("--stride", type=int, default=1, help="Keep every Nth reference point")
+parser.add_argument("--live-plot", action="store_true", help="Show the sweep while it runs")
+args = parser.parse_args()
+
+os.environ.setdefault("MPLBACKEND", "TkAgg" if args.live_plot else "Agg")
+
+import matplotlib.pyplot as plt  # noqa: E402
+
+import grax  # noqa: E402
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+import grating_definition as case  # noqa: E402
+
+SOLVER = "neviere"
+SOLVER_TITLE = "Nevière DM"
+
+
+def main() -> None:
+    """Run the sweep and write this solver's artifacts."""
+
+    grax.setup_logging(level="INFO", run_id=f"blazed_multilayer_sweep_{SOLVER}")
+    paths = case.output_paths(SOLVER)
+    reference = case.build_reference_grid(quick=args.quick, stride=args.stride)
+
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=case.DIFFRACTION_ORDER,
+        fourier_orders=case.QUICK_FOURIER_ORDERS if args.quick else case.FOURIER_ORDERS,
+        show_progress=True,
+        live_plot=args.live_plot,
+        live_plot_x_key="energy_ev",
+        live_plot_order_count=2,
+        live_plot_reference_data=reference[["Energy", "Efficiency(GR)"]].to_numpy(dtype=float),
+        on_error="fail_fast",
+        max_workers="auto",
+        checkpoint_dir=paths["checkpoint_dir"],
+        resume=False,
+        backend="numba",
+        solver=SOLVER,
+    )
+
+    results = list(runner.run_cases(case.build_cases(quick=args.quick, stride=args.stride)))
+    grax.write_all_orders_csv(results, paths["all_orders_csv"])
+    case.build_grating(quick=args.quick).plot_profile(paths["profile_plot"])
+    case.build_multilayer_stack().plot_schematic(paths["stack_plot"])
+
+    successful = [result for result in results if result.status == "ok"]
+    figure, axis = plt.subplots(figsize=(10, 6))
+    axis.plot(
+        [result.energy_ev for result in successful],
+        [result.selected_efficiency for result in successful],
+        "o-",
+        linewidth=1.0,
+        markersize=2.0,
+        label=f"grax ({SOLVER})",
+    )
+    axis.plot(
+        reference["Energy"],
+        reference["Efficiency(GR)"],
+        "s-",
+        linewidth=1.0,
+        markersize=2.0,
+        label="DiffraMod",
+    )
+    axis.set_xlabel("Energy (eV)")
+    axis.set_ylabel("Efficiency (2nd order)")
+    axis.set_title(f"Blazed Multilayer Energy-Angle Sweep, {SOLVER_TITLE}: 2nd Order")
+    axis.grid(True, alpha=0.3)
+    axis.legend(loc="best")
+    figure.tight_layout()
+    figure.savefig(paths["selected_order_plot"], dpi=150, bbox_inches="tight")
+    plt.close(figure)
+
+    print(f"Computed {len(successful)} energy-angle points with the {SOLVER} solver.")
+    print(f"All-orders CSV saved to: {paths['all_orders_csv']}")
+    print(f"Selected-order plot saved to: {paths['selected_order_plot']}")
+    print(f"Profile plot saved to: {paths['profile_plot']}")
+    print(f"Stack schematic saved to: {paths['stack_plot']}")
+
+
+# Spawned multiprocessing workers re-import this file by path; without the guard
+# each worker would re-run the whole sweep and recursively spawn more.
+if __name__ == "__main__":
+    main()
diff --git a/validation/blazed_multilayer/run_rcwa.py b/validation/blazed_multilayer/run_rcwa.py
new file mode 100644
index 0000000..111fac8
--- /dev/null
+++ b/validation/blazed_multilayer/run_rcwa.py
@@ -0,0 +1,109 @@
+"""Run the blazed 2400 l/mm multilayer energy-angle sweep with the RCWA solver.
+
+Writes ``results/blazed_multilayer_all_orders_rcwa.csv`` plus a second-order plot
+against the DiffractMod reference. The grating and the sweep grid come from
+``grating_definition.py``, which ``run_neviere.py`` also uses, so the two runs
+stay comparable.
+
+This is the most expensive validation case: at full resolution each point solves
+a 60-bilayer stack sliced at 0.01 nm. Use ``--stride`` to subsample the 1727
+reference points.
+
+```bash
+python validation/blazed_multilayer/run_rcwa.py --stride 10
+python validation/blazed_multilayer/run_rcwa.py --quick
+```
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+parser = argparse.ArgumentParser(description="Blazed multilayer energy-angle sweep (RCWA)")
+parser.add_argument("--quick", action="store_true", help="Run a few coarse points")
+parser.add_argument("--stride", type=int, default=1, help="Keep every Nth reference point")
+parser.add_argument("--live-plot", action="store_true", help="Show the sweep while it runs")
+args = parser.parse_args()
+
+os.environ.setdefault("MPLBACKEND", "TkAgg" if args.live_plot else "Agg")
+
+import matplotlib.pyplot as plt  # noqa: E402
+
+import grax  # noqa: E402
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+import grating_definition as case  # noqa: E402
+
+SOLVER = "rcwa"
+SOLVER_TITLE = "RCWA"
+
+
+def main() -> None:
+    """Run the sweep and write this solver's artifacts."""
+
+    grax.setup_logging(level="INFO", run_id=f"blazed_multilayer_sweep_{SOLVER}")
+    paths = case.output_paths(SOLVER)
+    reference = case.build_reference_grid(quick=args.quick, stride=args.stride)
+
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=case.DIFFRACTION_ORDER,
+        fourier_orders=case.QUICK_FOURIER_ORDERS if args.quick else case.FOURIER_ORDERS,
+        show_progress=True,
+        live_plot=args.live_plot,
+        live_plot_x_key="energy_ev",
+        live_plot_order_count=2,
+        live_plot_reference_data=reference[["Energy", "Efficiency(GR)"]].to_numpy(dtype=float),
+        on_error="fail_fast",
+        max_workers="auto",
+        checkpoint_dir=paths["checkpoint_dir"],
+        resume=False,
+        backend="numba",
+        solver=SOLVER,
+    )
+
+    results = list(runner.run_cases(case.build_cases(quick=args.quick, stride=args.stride)))
+    grax.write_all_orders_csv(results, paths["all_orders_csv"])
+    case.build_grating(quick=args.quick).plot_profile(paths["profile_plot"])
+    case.build_multilayer_stack().plot_schematic(paths["stack_plot"])
+
+    successful = [result for result in results if result.status == "ok"]
+    figure, axis = plt.subplots(figsize=(10, 6))
+    axis.plot(
+        [result.energy_ev for result in successful],
+        [result.selected_efficiency for result in successful],
+        "o-",
+        linewidth=1.0,
+        markersize=2.0,
+        label=f"grax ({SOLVER})",
+    )
+    axis.plot(
+        reference["Energy"],
+        reference["Efficiency(GR)"],
+        "s-",
+        linewidth=1.0,
+        markersize=2.0,
+        label="DiffraMod",
+    )
+    axis.set_xlabel("Energy (eV)")
+    axis.set_ylabel("Efficiency (2nd order)")
+    axis.set_title(f"Blazed Multilayer Energy-Angle Sweep, {SOLVER_TITLE}: 2nd Order")
+    axis.grid(True, alpha=0.3)
+    axis.legend(loc="best")
+    figure.tight_layout()
+    figure.savefig(paths["selected_order_plot"], dpi=150, bbox_inches="tight")
+    plt.close(figure)
+
+    print(f"Computed {len(successful)} energy-angle points with the {SOLVER} solver.")
+    print(f"All-orders CSV saved to: {paths['all_orders_csv']}")
+    print(f"Selected-order plot saved to: {paths['selected_order_plot']}")
+    print(f"Profile plot saved to: {paths['profile_plot']}")
+    print(f"Stack schematic saved to: {paths['stack_plot']}")
+
+
+# Spawned multiprocessing workers re-import this file by path; without the guard
+# each worker would re-run the whole sweep and recursively spawn more.
+if __name__ == "__main__":
+    main()
diff --git a/validation/laminar/comparison.py b/validation/laminar/comparison.py
index 3463094..246c8b6 100644
--- a/validation/laminar/comparison.py
+++ b/validation/laminar/comparison.py
@@ -3,6 +3,54 @@
 import matplotlib.pyplot as plt
 import pandas as pd
 
+
+# Both solvers' results are plotted when present. A fresh run writes
+# ``*_rcwa.csv`` / ``*_neviere.csv``; the unsuffixed CSV is the older checked-in
+# artifact and is only used as a fallback, because it predates several solver
+# changes and pairing it against a fresh run would show that drift as though it
+# were a difference between the two methods.
+SOLVER_LABELS = {"rcwa": "graxpy (RCWA)", "neviere": "graxpy (Nevière DM)"}
+# The two solvers agree to ~1e-11, so without a dashed overlay the second curve
+# hides the first completely and the plot looks as though one is missing.
+SOLVER_STYLES = {"rcwa": {"linestyle": "-"}, "neviere": {"linestyle": (0, (6, 4))}}
+
+
+def load_solver_curves(base_csv, order):
+    """Return (label, energy, efficiency, style) for each solver that has been run.
+
+    Args:
+        base_csv: Historical unsuffixed all-orders CSV path for this case.
+        order: Signed diffraction order to extract (reflected orders are negative).
+
+    Returns:
+        List of plottable curves, skipping solvers with no results yet.
+    """
+
+    curves = []
+    for solver in ("rcwa", "neviere"):
+        candidates = [base_csv.with_name(f"{base_csv.stem}_{solver}{base_csv.suffix}")]
+        if solver == "rcwa":
+            candidates.append(base_csv)
+        path = next((candidate for candidate in candidates if candidate.exists()), None)
+        if path is None:
+            print(f"  note: no {solver} results yet, skipping that curve")
+            continue
+        frame = pd.read_csv(path)
+        selected = frame[frame["order"] == order].sort_values("energy_ev")
+        if selected.empty:
+            print(f"  note: {path.name} has no order {order}, skipping that curve")
+            continue
+        print(f"  {SOLVER_LABELS[solver]:<22} <- {path.name}  ({len(selected)} points)")
+        curves.append(
+            (
+                SOLVER_LABELS[solver],
+                selected["energy_ev"],
+                selected["efficiency"],
+                dict(SOLVER_STYLES[solver]),
+            )
+        )
+    return curves
+
 # =========================
 # PLOT CONFIGURATION - Easy to adjust
 # =========================
@@ -37,12 +85,10 @@
     names=["Energy_eV", "Intensity"]
 ).dropna()
 # =========================
-# Reticolopy simulation (-1 order)
+# graxpy simulations (-1 order), one curve per solver that has been run
 # =========================
-df_sim = pd.read_csv(sim_file)
-df_sim_m1 = df_sim[df_sim["order"] == -1].sort_values("energy_ev")
-energy_sim = df_sim_m1["energy_ev"]
-eff_m1 = df_sim_m1["efficiency"]
+print("graxpy curves:")
+grax_curves = load_solver_curves(sim_file, order=-1)
 
 # =========================
 # RETICOLO simulation
@@ -83,8 +129,9 @@
 
 plt.plot(df_meas["Energy_eV"], df_meas["Intensity"],
          label="Measured data", linewidth=LINE_WIDTH)
-plt.plot(energy_sim, eff_m1,
-         label="Reticolopy", linewidth=LINE_WIDTH)
+for curve_label, curve_energy, curve_efficiency, curve_style in grax_curves:
+    plt.plot(curve_energy, curve_efficiency,
+             label=curve_label, linewidth=LINE_WIDTH, **curve_style)
 plt.plot(df_slag["PhotonEnergy_eV"], df_slag["DiffractionEfficiency"],
          label="Reticolo", linewidth=LINE_WIDTH)
 plt.plot(df_f3["Energy"], df_f3["efficiency_4deg"],
diff --git a/validation/laminar/comparison_laminar_fixed_angle.png b/validation/laminar/comparison_laminar_fixed_angle.png
index ba252c8..ae1f68e 100644
Binary files a/validation/laminar/comparison_laminar_fixed_angle.png and b/validation/laminar/comparison_laminar_fixed_angle.png differ
diff --git a/validation/laminar/fixed_angle_sweep.py b/validation/laminar/fixed_angle_sweep.py
deleted file mode 100644
index 3ca2fde..0000000
--- a/validation/laminar/fixed_angle_sweep.py
+++ /dev/null
@@ -1,131 +0,0 @@
-"""Laminar fixed-angle sweep using the centralized batch runner."""
-
-from __future__ import annotations
-
-import os
-import sys
-from pathlib import Path
-quick_mode = "--quick" in sys.argv
-LIVE_PLOT = False if quick_mode else True
-if LIVE_PLOT:
-    os.environ.setdefault("MPLBACKEND", "TkAgg")
-else:
-    os.environ.setdefault("MPLBACKEND", "Agg")
-
-import numpy as np  # noqa: E402
-import pandas as pd
-import matplotlib.pyplot as plt  # noqa: E402
-
-import grax  # noqa: E402
-
-repo_root = Path(__file__).resolve().parents[2]
-example_root = Path(__file__).resolve().parent
-optical_constants_dir = example_root / "optical_constants"
-results_dir = Path(__file__).resolve().parent / "results"
-results_dir.mkdir(parents=True, exist_ok=True)
-plot_path = results_dir / "laminar_fixed_angle_comparison.png"
-grating_plot_path = results_dir / "laminar_fixed_angle_profile.png"
-csv_path = results_dir / "laminar_fixed_angle_all_orders.csv"
-roughness_sigma_nm = 0.5
-silicon = pd.read_csv(
-    optical_constants_dir / "OC_Si_SSTR.dat",
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-silicon.attrs["name"] = "Si"
-platinum = pd.read_csv(
-    optical_constants_dir / "OC_Pt_SSTR.dat",
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-platinum.attrs["name"] = "Pt"
-
-carbon = pd.read_csv(
-    optical_constants_dir / "OC_C_SSTR.dat",
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-carbon.attrs["name"] = "C"
-
-grating = grax.LaminarGrating(
-    period_lpermm=400,
-    width_to_period_ratio=0.67,
-    depth_nm=14.9,
-    left_wall_angle_deg=15.0,
-    right_wall_angle_deg=15.0,
-    substrate_material=silicon,
-    layer_material=platinum,
-    layer_thickness_nm=28.77,
-    top_cap_material=carbon,
-    top_cap_thickness_nm=0.7,
-    z_resolution_nm=2.0 if quick_mode else 0.1,
-    x_resolution_nm=10.0 if quick_mode else 0.1,
-)
-energies = (
-    np.asarray([100.0, 300.0, 600.0], dtype=float)
-    if quick_mode
-    else np.arange(50.0, 650.1, 1.0)
-)
-cases = grax.fixed_angle_cases(
-    grating=grating,
-    energies_ev=energies,
-    grazing_angle_deg=4.0,
-    polarization="p",
-)
-cases = (
-    dict(case, label="fixed-angle", roughness_sigma_nm=roughness_sigma_nm)
-    for case in cases
-)
-
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=5 if quick_mode else 30,
-    show_progress=True,
-    live_plot=LIVE_PLOT,
-    live_plot_x_key="energy_ev",
-    live_plot_order_count=1,
-    live_plot_reference_data=grax.load_experimental_csv(
-        Path(__file__).resolve().parent / "measured_alpha4deg_order1.csv"
-    ),
-    on_error="fail_fast",
-    resume=False,
-    max_workers="auto",
-)
-grating.plot_profile(grating_plot_path)
-batch_result = list(runner.run_cases(cases))
-
-experimental = grax.load_experimental_csv(
-    Path(__file__).resolve().parent / "measured_alpha4deg_order1.csv"
-)
-figure, axis = plt.subplots(figsize=(10, 7))
-successful_cases = [case for case in batch_result if case.status == "ok"]
-axis.plot(
-    [case.energy_ev for case in successful_cases],
-    [case.selected_efficiency for case in successful_cases],
-    "b-o",
-    linewidth=0.8,
-    markersize=2.0,
-    label="simulation",
-)
-axis.plot(
-    experimental[:, 0],
-    experimental[:, 1],
-    "r-s",
-    linewidth=0.8,
-    markersize=2.0,
-    label="measurement",
-)
-axis.set_xlabel("Photon Energy (eV)")
-axis.set_ylabel("Diffraction Efficiency")
-axis.set_title("RCWA Simulation vs Experimental Data")
-axis.grid(True, alpha=0.3)
-axis.legend(loc="best")
-figure.tight_layout()
-figure.savefig(plot_path, dpi=150, bbox_inches="tight")
-plt.close(figure)
-grax.write_all_orders_csv(batch_result, csv_path)
-
-print(f"Computed {sum(case.status == 'ok' for case in batch_result)} energy points.")
-print(f"Comparison plot saved to: {plot_path}")
-print(f"Grating-period plot saved to: {grating_plot_path}")
-print(f"Simulation CSV saved to: {csv_path}")
diff --git a/validation/laminar/grating_definition.py b/validation/laminar/grating_definition.py
new file mode 100644
index 0000000..ebc7abb
--- /dev/null
+++ b/validation/laminar/grating_definition.py
@@ -0,0 +1,149 @@
+"""Grating and sweep definition for the laminar 400 l/mm validation case.
+
+Both `run_rcwa.py` and `run_neviere.py` import everything from here, so the two
+solver runs are guaranteed to see the same grating, the same energy grid and the
+same truncation. Anything defined per runner instead could drift between them,
+and the resulting comparison plot would show a "solver disagreement" that is
+really a mismatched sweep.
+
+Nothing in this module depends on which solver is used.
+"""
+
+from __future__ import annotations
+
+from functools import lru_cache
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+
+import grax
+
+CASE_ROOT = Path(__file__).resolve().parent
+OPTICAL_CONSTANTS_DIR = CASE_ROOT / "optical_constants"
+RESULTS_DIR = CASE_ROOT / "results"
+MEASUREMENT_FILE = CASE_ROOT / "measured_alpha4deg_order1.csv"
+
+# Sweep settings shared by both solvers.
+GRAZING_ANGLE_DEG = 4.0
+POLARIZATION = "p"
+DIFFRACTION_ORDER = 1
+FOURIER_ORDERS = 30
+ROUGHNESS_SIGMA_NM = 0.5
+
+QUICK_ENERGIES_EV = np.asarray([100.0, 300.0, 600.0], dtype=float)
+QUICK_FOURIER_ORDERS = 5
+
+
+@lru_cache(maxsize=None)
+def load_optical_constants(name: str) -> pd.DataFrame:
+    """Return one optical-constants table by material name.
+
+    Cached so repeated calls return the *same* object. ``MultilayerStack``
+    identifies ``top_material`` by matching it against ``material_a`` or
+    ``material_b``, which fails if each call hands back a fresh DataFrame.
+
+    Args:
+        name: Material name matching an ``OC_<name>_SSTR.dat`` file.
+
+    Returns:
+        Optical-constants table tagged with the material name.
+    """
+
+    table = pd.read_csv(
+        OPTICAL_CONSTANTS_DIR / f"OC_{name}_SSTR.dat",
+        sep=r"\s*,\s*|\s+",
+        engine="python",
+    )
+    table.attrs["name"] = name
+    return table
+
+
+def build_grating(*, quick: bool = False) -> grax.LaminarGrating:
+    """Return the laminar grating for this validation case.
+
+    Args:
+        quick: Use coarse resolutions for a fast smoke run.
+
+    Returns:
+        Configured laminar grating.
+    """
+
+    return grax.LaminarGrating(
+        period_lpermm=400,
+        width_to_period_ratio=0.67,
+        depth_nm=14.9,
+        left_wall_angle_deg=15.0,
+        right_wall_angle_deg=15.0,
+        substrate_material=load_optical_constants("Si"),
+        layer_material=load_optical_constants("Pt"),
+        layer_thickness_nm=28.77,
+        top_cap_material=load_optical_constants("C"),
+        top_cap_thickness_nm=0.7,
+        z_resolution_nm=2.0 if quick else 0.1,
+        x_resolution_nm=10.0 if quick else 0.1,
+    )
+
+
+def build_energies_ev(*, quick: bool = False, stride: int = 1) -> np.ndarray:
+    """Return the photon energies swept by this case.
+
+    Args:
+        quick: Use the three-point smoke grid.
+        stride: Keep every Nth energy. Must be >= 1.
+
+    Returns:
+        Photon energies in electronvolts.
+    """
+
+    if stride < 1:
+        raise ValueError("stride must be >= 1.")
+    energies = QUICK_ENERGIES_EV if quick else np.arange(50.0, 650.1, 1.0)
+    return energies[::stride]
+
+
+def build_cases(*, quick: bool = False, stride: int = 1):
+    """Return the batch cases for this sweep, identical for either solver.
+
+    Args:
+        quick: Use the coarse smoke configuration.
+        stride: Keep every Nth energy.
+
+    Returns:
+        Iterable of case dictionaries.
+    """
+
+    grating = build_grating(quick=quick)
+    cases = grax.fixed_angle_cases(
+        grating=grating,
+        energies_ev=build_energies_ev(quick=quick, stride=stride),
+        grazing_angle_deg=GRAZING_ANGLE_DEG,
+        polarization=POLARIZATION,
+    )
+    return (
+        dict(case, label="fixed-angle", roughness_sigma_nm=ROUGHNESS_SIGMA_NM)
+        for case in cases
+    )
+
+
+def output_paths(solver: str) -> dict[str, Path]:
+    """Return the output paths for one solver's run.
+
+    The checked-in artifacts under ``results/`` keep their historical unsuffixed
+    names; every fresh run writes to a ``_rcwa`` or ``_neviere`` sibling.
+
+    Args:
+        solver: ``"rcwa"`` or ``"neviere"``.
+
+    Returns:
+        Mapping of output name to path.
+    """
+
+    if solver not in ("rcwa", "neviere"):
+        raise ValueError(f"solver must be 'rcwa' or 'neviere', got {solver!r}.")
+    RESULTS_DIR.mkdir(parents=True, exist_ok=True)
+    return {
+        "all_orders_csv": RESULTS_DIR / f"laminar_fixed_angle_all_orders_{solver}.csv",
+        "measurement_plot": RESULTS_DIR / f"laminar_fixed_angle_comparison_{solver}.png",
+        "profile_plot": RESULTS_DIR / "laminar_fixed_angle_profile.png",
+    }
diff --git a/validation/laminar/results/laminar_fixed_angle_all_orders_neviere.csv b/validation/laminar/results/laminar_fixed_angle_all_orders_neviere.csv
new file mode 100644
index 0000000..bc48169
--- /dev/null
+++ b/validation/laminar/results/laminar_fixed_angle_all_orders_neviere.csv
@@ -0,0 +1,36662 @@
+case_id,energy_ev,grazing_angle_deg,order,efficiency,diffraction_angle_deg
+fixed-00000000,50.0,4.0,-30,1.6344096707473923e-05,45.57202919717884
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+fixed-00000000,50.0,4.0,-27,1.8871051636145303e-05,43.13311462865228
+fixed-00000000,50.0,4.0,-26,2.132782891117861e-05,42.29535532171013
+fixed-00000000,50.0,4.0,-25,2.829963480759943e-05,41.443908863445074
+fixed-00000000,50.0,4.0,-24,2.606510132482026e-05,40.57788377207388
+fixed-00000000,50.0,4.0,-23,2.9825538453061835e-05,39.69629578466584
+fixed-00000000,50.0,4.0,-22,3.8477889981098926e-05,38.79805365811375
+fixed-00000000,50.0,4.0,-21,3.830480738535919e-05,37.881942056276806
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diff --git a/validation/laminar/results/laminar_fixed_angle_all_orders_rcwa.csv b/validation/laminar/results/laminar_fixed_angle_all_orders_rcwa.csv
new file mode 100644
index 0000000..df3d940
--- /dev/null
+++ b/validation/laminar/results/laminar_fixed_angle_all_orders_rcwa.csv
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diff --git a/validation/laminar/results/laminar_fixed_angle_all_orders_solver_comparison.csv b/validation/laminar/results/laminar_fixed_angle_all_orders_solver_comparison.csv
new file mode 100644
index 0000000..b39ecb4
--- /dev/null
+++ b/validation/laminar/results/laminar_fixed_angle_all_orders_solver_comparison.csv
@@ -0,0 +1,4 @@
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diff --git a/validation/laminar/results/laminar_fixed_angle_comparison_neviere.png b/validation/laminar/results/laminar_fixed_angle_comparison_neviere.png
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index 0000000..34e55ad
Binary files /dev/null and b/validation/laminar/results/laminar_fixed_angle_comparison_neviere.png differ
diff --git a/validation/laminar/results/laminar_fixed_angle_comparison_rcwa.png b/validation/laminar/results/laminar_fixed_angle_comparison_rcwa.png
new file mode 100644
index 0000000..95ac5ee
Binary files /dev/null and b/validation/laminar/results/laminar_fixed_angle_comparison_rcwa.png differ
diff --git a/validation/laminar/run_neviere.py b/validation/laminar/run_neviere.py
new file mode 100644
index 0000000..50f537c
--- /dev/null
+++ b/validation/laminar/run_neviere.py
@@ -0,0 +1,100 @@
+"""Run the laminar 400 l/mm fixed-angle sweep with the Nevière differential method.
+
+Writes ``results/laminar_fixed_angle_all_orders_neviere.csv`` plus a plot against
+the measured curve. The grating and the sweep grid come from
+``grating_definition.py``, which ``run_rcwa.py`` also uses, so the two runs
+stay comparable.
+
+```bash
+python validation/laminar/run_neviere.py
+python validation/laminar/run_neviere.py --quick
+```
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+parser = argparse.ArgumentParser(description="Laminar 400 l/mm fixed-angle sweep (Nevière)")
+parser.add_argument("--quick", action="store_true", help="Run a few coarse energy points")
+parser.add_argument("--stride", type=int, default=1, help="Keep every Nth energy point")
+parser.add_argument("--live-plot", action="store_true", help="Show the sweep while it runs")
+args = parser.parse_args()
+
+os.environ.setdefault("MPLBACKEND", "TkAgg" if args.live_plot else "Agg")
+
+import matplotlib.pyplot as plt  # noqa: E402
+
+import grax  # noqa: E402
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+import grating_definition as case  # noqa: E402
+
+SOLVER = "neviere"
+
+
+def main() -> None:
+    """Run the sweep and write this solver's artifacts."""
+
+    paths = case.output_paths(SOLVER)
+    experimental = grax.load_experimental_csv(case.MEASUREMENT_FILE)
+
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=case.DIFFRACTION_ORDER,
+        fourier_orders=case.QUICK_FOURIER_ORDERS if args.quick else case.FOURIER_ORDERS,
+        show_progress=True,
+        live_plot=args.live_plot,
+        live_plot_x_key="energy_ev",
+        live_plot_order_count=1,
+        live_plot_reference_data=experimental,
+        on_error="fail_fast",
+        resume=False,
+        max_workers="auto",
+        solver=SOLVER,
+    )
+
+    case.build_grating(quick=args.quick).plot_profile(paths["profile_plot"])
+    results = list(runner.run_cases(case.build_cases(quick=args.quick, stride=args.stride)))
+    successful = [result for result in results if result.status == "ok"]
+
+    figure, axis = plt.subplots(figsize=(10, 7))
+    axis.plot(
+        [result.energy_ev for result in successful],
+        [result.selected_efficiency for result in successful],
+        "b-o",
+        linewidth=0.8,
+        markersize=2.0,
+        label=f"simulation ({SOLVER})",
+    )
+    axis.plot(
+        experimental[:, 0],
+        experimental[:, 1],
+        "r-s",
+        linewidth=0.8,
+        markersize=2.0,
+        label="measurement",
+    )
+    axis.set_xlabel("Photon Energy (eV)")
+    axis.set_ylabel("Diffraction Efficiency")
+    axis.set_title("Nevière Differential-Method Simulation vs Experimental Data")
+    axis.grid(True, alpha=0.3)
+    axis.legend(loc="best")
+    figure.tight_layout()
+    figure.savefig(paths["measurement_plot"], dpi=150, bbox_inches="tight")
+    plt.close(figure)
+
+    grax.write_all_orders_csv(results, paths["all_orders_csv"])
+
+    print(f"Computed {len(successful)} energy points with the {SOLVER} solver.")
+    print(f"All-orders CSV saved to: {paths['all_orders_csv']}")
+    print(f"Measurement comparison saved to: {paths['measurement_plot']}")
+    print(f"Grating profile saved to: {paths['profile_plot']}")
+
+
+# Spawned multiprocessing workers re-import this file by path; without the guard
+# each worker would re-run the whole sweep and recursively spawn more.
+if __name__ == "__main__":
+    main()
diff --git a/validation/laminar/run_rcwa.py b/validation/laminar/run_rcwa.py
new file mode 100644
index 0000000..aab2519
--- /dev/null
+++ b/validation/laminar/run_rcwa.py
@@ -0,0 +1,100 @@
+"""Run the laminar 400 l/mm fixed-angle sweep with the RCWA solver.
+
+Writes ``results/laminar_fixed_angle_all_orders_rcwa.csv`` plus a plot against
+the measured curve. The grating and the sweep grid come from
+``grating_definition.py``, which ``run_neviere.py`` also uses, so the two runs
+stay comparable.
+
+```bash
+python validation/laminar/run_rcwa.py
+python validation/laminar/run_rcwa.py --quick
+```
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+parser = argparse.ArgumentParser(description="Laminar 400 l/mm fixed-angle sweep (RCWA)")
+parser.add_argument("--quick", action="store_true", help="Run a few coarse energy points")
+parser.add_argument("--stride", type=int, default=1, help="Keep every Nth energy point")
+parser.add_argument("--live-plot", action="store_true", help="Show the sweep while it runs")
+args = parser.parse_args()
+
+os.environ.setdefault("MPLBACKEND", "TkAgg" if args.live_plot else "Agg")
+
+import matplotlib.pyplot as plt  # noqa: E402
+
+import grax  # noqa: E402
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+import grating_definition as case  # noqa: E402
+
+SOLVER = "rcwa"
+
+
+def main() -> None:
+    """Run the sweep and write this solver's artifacts."""
+
+    paths = case.output_paths(SOLVER)
+    experimental = grax.load_experimental_csv(case.MEASUREMENT_FILE)
+
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=case.DIFFRACTION_ORDER,
+        fourier_orders=case.QUICK_FOURIER_ORDERS if args.quick else case.FOURIER_ORDERS,
+        show_progress=True,
+        live_plot=args.live_plot,
+        live_plot_x_key="energy_ev",
+        live_plot_order_count=1,
+        live_plot_reference_data=experimental,
+        on_error="fail_fast",
+        resume=False,
+        max_workers="auto",
+        solver=SOLVER,
+    )
+
+    case.build_grating(quick=args.quick).plot_profile(paths["profile_plot"])
+    results = list(runner.run_cases(case.build_cases(quick=args.quick, stride=args.stride)))
+    successful = [result for result in results if result.status == "ok"]
+
+    figure, axis = plt.subplots(figsize=(10, 7))
+    axis.plot(
+        [result.energy_ev for result in successful],
+        [result.selected_efficiency for result in successful],
+        "b-o",
+        linewidth=0.8,
+        markersize=2.0,
+        label=f"simulation ({SOLVER})",
+    )
+    axis.plot(
+        experimental[:, 0],
+        experimental[:, 1],
+        "r-s",
+        linewidth=0.8,
+        markersize=2.0,
+        label="measurement",
+    )
+    axis.set_xlabel("Photon Energy (eV)")
+    axis.set_ylabel("Diffraction Efficiency")
+    axis.set_title("RCWA Simulation vs Experimental Data")
+    axis.grid(True, alpha=0.3)
+    axis.legend(loc="best")
+    figure.tight_layout()
+    figure.savefig(paths["measurement_plot"], dpi=150, bbox_inches="tight")
+    plt.close(figure)
+
+    grax.write_all_orders_csv(results, paths["all_orders_csv"])
+
+    print(f"Computed {len(successful)} energy points with the {SOLVER} solver.")
+    print(f"All-orders CSV saved to: {paths['all_orders_csv']}")
+    print(f"Measurement comparison saved to: {paths['measurement_plot']}")
+    print(f"Grating profile saved to: {paths['profile_plot']}")
+
+
+# Spawned multiprocessing workers re-import this file by path; without the guard
+# each worker would re-run the whole sweep and recursively spawn more.
+if __name__ == "__main__":
+    main()
diff --git a/validation/laminar_150lmm/comparison_laminar_150lmm_monochromator.png b/validation/laminar_150lmm/comparison_laminar_150lmm_monochromator.png
index 5aa7b11..d504184 100644
Binary files a/validation/laminar_150lmm/comparison_laminar_150lmm_monochromator.png and b/validation/laminar_150lmm/comparison_laminar_150lmm_monochromator.png differ
diff --git a/validation/laminar_150lmm/comparison_laminar_150lmm_monochromator.py b/validation/laminar_150lmm/comparison_laminar_150lmm_monochromator.py
index 3f5a618..091bd91 100644
--- a/validation/laminar_150lmm/comparison_laminar_150lmm_monochromator.py
+++ b/validation/laminar_150lmm/comparison_laminar_150lmm_monochromator.py
@@ -8,6 +8,54 @@
 import pandas as pd
 
 
+# Both solvers' results are plotted when present. A fresh run writes
+# ``*_rcwa.csv`` / ``*_neviere.csv``; the unsuffixed CSV is the older checked-in
+# artifact and is only used as a fallback, because it predates several solver
+# changes and pairing it against a fresh run would show that drift as though it
+# were a difference between the two methods.
+SOLVER_LABELS = {"rcwa": "graxpy (RCWA)", "neviere": "graxpy (Nevière DM)"}
+# The two solvers agree to ~1e-11, so without a dashed overlay the second curve
+# hides the first completely and the plot looks as though one is missing.
+SOLVER_STYLES = {"rcwa": {"linestyle": "-"}, "neviere": {"linestyle": (0, (6, 4))}}
+
+
+def load_solver_curves(base_csv, order):
+    """Return (label, energy, efficiency, style) for each solver that has been run.
+
+    Args:
+        base_csv: Historical unsuffixed all-orders CSV path for this case.
+        order: Signed diffraction order to extract (reflected orders are negative).
+
+    Returns:
+        List of plottable curves, skipping solvers with no results yet.
+    """
+
+    curves = []
+    for solver in ("rcwa", "neviere"):
+        candidates = [base_csv.with_name(f"{base_csv.stem}_{solver}{base_csv.suffix}")]
+        if solver == "rcwa":
+            candidates.append(base_csv)
+        path = next((candidate for candidate in candidates if candidate.exists()), None)
+        if path is None:
+            print(f"  note: no {solver} results yet, skipping that curve")
+            continue
+        frame = pd.read_csv(path)
+        selected = frame[frame["order"] == order].sort_values("energy_ev")
+        if selected.empty:
+            print(f"  note: {path.name} has no order {order}, skipping that curve")
+            continue
+        print(f"  {SOLVER_LABELS[solver]:<22} <- {path.name}  ({len(selected)} points)")
+        curves.append(
+            (
+                SOLVER_LABELS[solver],
+                selected["energy_ev"],
+                selected["efficiency"],
+                dict(SOLVER_STYLES[solver]),
+            )
+        )
+    return curves
+
+
 example_root = Path(__file__).resolve().parent
 results_file = example_root / "results" / "laminar_150lmm_monochromator_all_orders.csv"
 simulation_dir = example_root / "simulation"
@@ -68,20 +116,22 @@ def _load_external_table(path: Path) -> tuple[pd.Series, list[tuple[str, pd.Seri
     return energy_series, cleaned_series
 
 
-df_grax = pd.read_csv(results_file)
-df_grax_m1 = df_grax[df_grax["order"] == -1].copy().sort_values("energy_ev")
+print("graxpy curves:")
+grax_curves = load_solver_curves(results_file, order=-1)
 
 external_files = sorted([path for path in simulation_dir.iterdir() if path.is_file()])
 if not external_files:
     raise FileNotFoundError(f"No external files found in {simulation_dir}")
 
 figure, axis = plt.subplots(figsize=(12, 8))
-axis.plot(
-    df_grax_m1["energy_ev"],
-    df_grax_m1["efficiency"],
-    label="grax (order -1 -> +1)",
-    linewidth=2.2,
-)
+for curve_label, curve_energy, curve_efficiency, curve_style in grax_curves:
+    axis.plot(
+        curve_energy,
+        curve_efficiency,
+        label=f"{curve_label}, order -1 -> +1",
+        linewidth=2.2,
+        **curve_style,
+    )
 
 for external_path in external_files:
     if not FILE_PLOT_OPTIONS.get(external_path.name, False):
diff --git a/validation/laminar_150lmm/grating_definition.py b/validation/laminar_150lmm/grating_definition.py
new file mode 100644
index 0000000..89a67ac
--- /dev/null
+++ b/validation/laminar_150lmm/grating_definition.py
@@ -0,0 +1,179 @@
+"""Grating and sweep definition for the laminar 150 l/mm validation case.
+
+Both `run_rcwa.py` and `run_neviere.py` import everything from here, so the two
+solver runs are guaranteed to see the same grating, the same energy grid and the
+same truncation. Anything defined per runner instead could drift between them,
+and the resulting comparison plot would show a "solver disagreement" that is
+really a mismatched sweep.
+
+Nothing in this module depends on which solver is used.
+"""
+
+from __future__ import annotations
+
+from functools import lru_cache
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+
+import grax
+
+CASE_ROOT = Path(__file__).resolve().parent
+OPTICAL_CONSTANTS_DIR = CASE_ROOT / "optical_constants"
+RESULTS_DIR = CASE_ROOT / "results"
+
+# Grating geometry.
+PERIOD_LPERMM = 150
+WIDTH_TO_PERIOD_RATIO = 0.65
+DEPTH_NM = 60.0
+WALL_ANGLE_DEG = 10.0
+LAYER_THICKNESS_NM = 30.0
+
+# Sweep settings shared by both solvers.
+CFF = 1.45
+POLARIZATION = "p"
+DIFFRACTION_ORDER = 1
+FOURIER_ORDERS = 10
+PLOT_ORDERS = [1, 2, 3]
+
+QUICK_ENERGIES_EV = np.asarray([100.0, 500.0, 900.0], dtype=float)
+QUICK_FOURIER_ORDERS = 5
+
+
+@lru_cache(maxsize=None)
+def load_optical_constants(name: str) -> pd.DataFrame:
+    """Return one optical-constants table by material name.
+
+    Cached so repeated calls return the *same* object. ``MultilayerStack``
+    identifies ``top_material`` by matching it against ``material_a`` or
+    ``material_b``, which fails if each call hands back a fresh DataFrame.
+
+    Args:
+        name: Material name matching an ``OC_<name>_SSTR.dat`` file.
+
+    Returns:
+        Optical-constants table tagged with the material name.
+    """
+
+    table = pd.read_csv(
+        OPTICAL_CONSTANTS_DIR / f"OC_{name}_SSTR.dat",
+        sep=r"\s*,\s*|\s+",
+        engine="python",
+    )
+    table.attrs["name"] = name
+    return table
+
+
+def build_grating(*, quick: bool = False) -> grax.LaminarGrating:
+    """Return the laminar grating for this validation case.
+
+    Args:
+        quick: Use coarse resolutions for a fast smoke run.
+
+    Returns:
+        Configured laminar grating.
+    """
+
+    return grax.LaminarGrating(
+        period_lpermm=PERIOD_LPERMM,
+        width_to_period_ratio=WIDTH_TO_PERIOD_RATIO,
+        depth_nm=DEPTH_NM,
+        left_wall_angle_deg=WALL_ANGLE_DEG,
+        right_wall_angle_deg=WALL_ANGLE_DEG,
+        substrate_material=load_optical_constants("Si"),
+        layer_material=load_optical_constants("Au"),
+        layer_thickness_nm=LAYER_THICKNESS_NM,
+        top_cap_material=None,
+        top_cap_thickness_nm=0.0,
+        x_resolution_nm=2.0 if quick else 0.3,
+        z_resolution_nm=2.0 if quick else 0.3,
+    )
+
+
+def build_energies_ev(*, quick: bool = False, stride: int = 1) -> np.ndarray:
+    """Return the photon energies swept by this case.
+
+    Matches ``RR-test-lGR150-gd60-nonSP-20_dm_de_r_m1_single.dat``: 10 eV to
+    1000 eV in 2 eV steps.
+
+    Args:
+        quick: Use the three-point smoke grid.
+        stride: Keep every Nth energy. Must be >= 1.
+
+    Returns:
+        Photon energies in electronvolts.
+    """
+
+    if stride < 1:
+        raise ValueError("stride must be >= 1.")
+    energies = QUICK_ENERGIES_EV if quick else np.arange(10.0, 1000.1, 2.0)
+    return energies[::stride]
+
+
+def build_cases(*, quick: bool = False, stride: int = 1):
+    """Return the batch cases for this sweep, identical for either solver.
+
+    Args:
+        quick: Use the coarse smoke configuration.
+        stride: Keep every Nth energy.
+
+    Returns:
+        Iterable of case dictionaries.
+    """
+
+    return grax.monochromator_cases(
+        grating=build_grating(quick=quick),
+        energies_ev=build_energies_ev(quick=quick, stride=stride),
+        diffraction_order=DIFFRACTION_ORDER,
+        cff=CFF,
+        polarization=POLARIZATION,
+    )
+
+
+def sweep_metadata(solver: str) -> dict[str, object]:
+    """Return checkpoint metadata describing this sweep.
+
+    Args:
+        solver: Solver used for the run.
+
+    Returns:
+        JSON-serializable metadata mapping.
+    """
+
+    return {
+        "description": "Laminar 150 l/mm monochromator sweep",
+        "solver": solver,
+        "period_lpermm": PERIOD_LPERMM,
+        "width_to_period_ratio": WIDTH_TO_PERIOD_RATIO,
+        "depth_nm": DEPTH_NM,
+        "left_wall_angle_deg": WALL_ANGLE_DEG,
+        "right_wall_angle_deg": WALL_ANGLE_DEG,
+        "layer_thickness_nm": LAYER_THICKNESS_NM,
+        "diffraction_order": DIFFRACTION_ORDER,
+        "cff": CFF,
+        "fourier_orders": FOURIER_ORDERS,
+    }
+
+
+def output_paths(solver: str) -> dict[str, Path]:
+    """Return the output paths for one solver's run.
+
+    The checked-in artifacts under ``results/`` keep their historical unsuffixed
+    names; every fresh run writes to a ``_rcwa`` or ``_neviere`` sibling.
+
+    Args:
+        solver: ``"rcwa"`` or ``"neviere"``.
+
+    Returns:
+        Mapping of output name to path.
+    """
+
+    if solver not in ("rcwa", "neviere"):
+        raise ValueError(f"solver must be 'rcwa' or 'neviere', got {solver!r}.")
+    RESULTS_DIR.mkdir(parents=True, exist_ok=True)
+    return {
+        "all_orders_csv": RESULTS_DIR / f"laminar_150lmm_monochromator_all_orders_{solver}.csv",
+        "orders_plot": RESULTS_DIR / f"laminar_150lmm_monochromator_orders_1_3_{solver}.png",
+        "profile_plot": RESULTS_DIR / "laminar_150lmm_monochromator_profile.png",
+    }
diff --git a/validation/laminar_150lmm/laminar_150lmm_monochromator_sweep.py b/validation/laminar_150lmm/laminar_150lmm_monochromator_sweep.py
deleted file mode 100644
index e74881b..0000000
--- a/validation/laminar_150lmm/laminar_150lmm_monochromator_sweep.py
+++ /dev/null
@@ -1,111 +0,0 @@
-"""Monochromator sweep for a 150 l/mm laminar grating (CFF=2.25)."""
-
-from __future__ import annotations
-
-from pathlib import Path
-
-import numpy as np
-import pandas as pd
-
-import grax
-
-
-grax.setup_logging(level="INFO", run_id="laminar_150lmm_monochromator")
-
-example_root = Path(__file__).resolve().parent
-optical_constants_dir = example_root / "optical_constants"
-results_dir = example_root / "results"
-results_dir.mkdir(parents=True, exist_ok=True)
-
-csv_path = results_dir / "laminar_150lmm_monochromator_all_orders.csv"
-orders_plot_path = results_dir / "laminar_150lmm_monochromator_orders_1_3.png"
-profile_plot_path = results_dir / "laminar_150lmm_monochromator_profile.png"
-
-silicon = pd.read_csv(
-    optical_constants_dir / "OC_Si_SSTR.dat",
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-silicon.attrs["name"] = "Si"
-
-gold = pd.read_csv(
-    optical_constants_dir / "OC_Au_SSTR.dat",
-    sep=r"\s*,\s*|\s+",
-    engine="python",
-)
-gold.attrs["name"] = "Au"
-
-# Requested geometry and coating parameters.
-grating = grax.LaminarGrating(
-    period_lpermm=150,
-    width_to_period_ratio=0.65,
-    depth_nm=60.0,
-    left_wall_angle_deg=10.0,
-    right_wall_angle_deg=10.0,
-    substrate_material=silicon,
-    layer_material=gold,
-    layer_thickness_nm=30.0,
-    top_cap_material=None,
-    top_cap_thickness_nm=0.0,
-    x_resolution_nm=0.3,
-    z_resolution_nm=0.3,
-)
-
-# Match RR-test-lGR150-gd60-nonSP-20_dm_de_r_m1_single.dat:
-# 10 eV to 1000 eV in 2 eV steps.
-energies_ev = np.arange(10.0, 1000.1, 2.0)
-
-cases = grax.monochromator_cases(
-    grating=grating,
-    energies_ev=energies_ev,
-    diffraction_order=1,
-    cff=1.45,
-    polarization="p",
-)
-
-runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=10,
-    show_progress=True,
-    live_plot=True,
-    live_plot_x_key="energy_ev",
-    live_plot_order_count=3,
-    on_error="fail_fast",
-    max_workers='auto',
-    resume=False,
-    backend="numba",
-)
-
-grating.plot_profile(profile_plot_path)
-batch_result = list(
-    runner.run_cases(
-        cases,
-        metadata={
-            "description": "Laminar 150 l/mm monochromator sweep",
-            "period_lpermm": 150,
-            "width_to_period_ratio": 0.65,
-            "depth_nm": 60.0,
-            "left_wall_angle_deg": 10.0,
-            "right_wall_angle_deg": 10.0,
-            "layer_thickness_nm": 30.0,
-            "diffraction_order": 1,
-            "cff": 1.45,
-            "fourier_orders": 5,
-            "x_resolution_nm": 1.0,
-            "z_resolution_nm": 1.0,
-        },
-    )
-)
-
-grax.write_all_orders_csv(batch_result, csv_path)
-grax.plot_order_subset(
-    batch_result,
-    orders_plot_path,
-    diffraction_orders=[1, 2, 3],
-    title="Laminar 150 l/mm Monochromator Sweep: Orders 1-3",
-)
-
-print(f"Computed {sum(case.status == 'ok' for case in batch_result)} monochromator points.")
-print(f"Monochromator all-orders CSV saved to: {csv_path}")
-print(f"Monochromator orders plot saved to: {orders_plot_path}")
-print(f"Grating profile plot saved to: {profile_plot_path}")
diff --git a/validation/laminar_150lmm/parameter_influence_study.py b/validation/laminar_150lmm/parameter_influence_study.py
index de05993..3610820 100644
--- a/validation/laminar_150lmm/parameter_influence_study.py
+++ b/validation/laminar_150lmm/parameter_influence_study.py
@@ -59,8 +59,8 @@
 )
 
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=DIFFRACTION_ORDER,
-    default_fourier_orders=5,
+    diffraction_order=DIFFRACTION_ORDER,
+    fourier_orders=5,
     show_progress=True,
     on_error="continue",
     resume=False,
diff --git a/validation/laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_neviere.csv b/validation/laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_neviere.csv
new file mode 100644
index 0000000..b32c21b
--- /dev/null
+++ b/validation/laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_neviere.csv
@@ -0,0 +1,10417 @@
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diff --git a/validation/laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_rcwa.csv b/validation/laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_rcwa.csv
new file mode 100644
index 0000000..4c272d7
--- /dev/null
+++ b/validation/laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_rcwa.csv
@@ -0,0 +1,10417 @@
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+mono-00000495,1000.0,1.052294672006198,-2,0.011458188801512573,1.8840453210353019
+mono-00000495,1000.0,1.052294672006198,-1,0.08197287820241468,1.5259218749243644
+mono-00000495,1000.0,1.052294672006198,0,0.11140182835526377,1.0522946720062833
+mono-00000495,1000.0,1.052294672006198,1,0.0,0.0
+mono-00000495,1000.0,1.052294672006198,2,0.0,0.0
+mono-00000495,1000.0,1.052294672006198,3,0.0,0.0
+mono-00000495,1000.0,1.052294672006198,4,0.0,0.0
+mono-00000495,1000.0,1.052294672006198,5,0.0,0.0
+mono-00000495,1000.0,1.052294672006198,6,0.0,0.0
+mono-00000495,1000.0,1.052294672006198,7,0.0,0.0
+mono-00000495,1000.0,1.052294672006198,8,0.0,0.0
+mono-00000495,1000.0,1.052294672006198,9,0.0,0.0
+mono-00000495,1000.0,1.052294672006198,10,0.0,0.0
diff --git a/validation/laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_solver_comparison.csv b/validation/laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_solver_comparison.csv
new file mode 100644
index 0000000..98e2be4
--- /dev/null
+++ b/validation/laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_solver_comparison.csv
@@ -0,0 +1,4 @@
+order,shared_points,max_abs_deviation,mean_abs_deviation,rms_deviation,peak_rcwa_efficiency,max_deviation_over_peak
+1,496,3.907402179592623e-12,1.33323249254032e-12,1.5885059971831317e-12,0.3312888862554278,1.17945465172652e-11
+2,496,2.8551987163449866e-12,1.1204346326250369e-12,1.3768599084375314e-12,0.1156422834950796,2.4689919898256513e-11
+3,496,1.4454002231212293e-12,5.260042871877755e-13,6.740461294417477e-13,0.0424249941257306,3.406954444914347e-11
diff --git a/validation/laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_solver_comparison.png b/validation/laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_solver_comparison.png
new file mode 100644
index 0000000..9395769
Binary files /dev/null and b/validation/laminar_150lmm/results/laminar_150lmm_monochromator_all_orders_solver_comparison.png differ
diff --git a/validation/laminar_150lmm/results/laminar_150lmm_monochromator_orders_1_3_neviere.png b/validation/laminar_150lmm/results/laminar_150lmm_monochromator_orders_1_3_neviere.png
new file mode 100644
index 0000000..de467cb
Binary files /dev/null and b/validation/laminar_150lmm/results/laminar_150lmm_monochromator_orders_1_3_neviere.png differ
diff --git a/validation/laminar_150lmm/results/laminar_150lmm_monochromator_orders_1_3_rcwa.png b/validation/laminar_150lmm/results/laminar_150lmm_monochromator_orders_1_3_rcwa.png
new file mode 100644
index 0000000..1d95e3a
Binary files /dev/null and b/validation/laminar_150lmm/results/laminar_150lmm_monochromator_orders_1_3_rcwa.png differ
diff --git a/validation/laminar_150lmm/run_neviere.py b/validation/laminar_150lmm/run_neviere.py
new file mode 100644
index 0000000..22e243f
--- /dev/null
+++ b/validation/laminar_150lmm/run_neviere.py
@@ -0,0 +1,84 @@
+"""Run the laminar 150 l/mm monochromator sweep with the Nevière differential method.
+
+Writes ``results/laminar_150lmm_monochromator_all_orders_neviere.csv`` plus an
+orders 1-3 plot. The grating and the sweep grid come from
+``grating_definition.py``, which ``run_rcwa.py`` also uses, so the two runs
+stay comparable.
+
+```bash
+python validation/laminar_150lmm/run_neviere.py
+python validation/laminar_150lmm/run_neviere.py --quick
+```
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+parser = argparse.ArgumentParser(description="Laminar 150 l/mm monochromator sweep (Nevière)")
+parser.add_argument("--quick", action="store_true", help="Run a few coarse energy points")
+parser.add_argument("--stride", type=int, default=1, help="Keep every Nth energy point")
+parser.add_argument("--live-plot", action="store_true", help="Show the sweep while it runs")
+args = parser.parse_args()
+
+os.environ.setdefault("MPLBACKEND", "TkAgg" if args.live_plot else "Agg")
+
+import grax  # noqa: E402
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+import grating_definition as case  # noqa: E402
+
+SOLVER = "neviere"
+SOLVER_TITLE = "Nevière DM"
+
+
+def main() -> None:
+    """Run the sweep and write this solver's artifacts."""
+
+    grax.setup_logging(level="INFO", run_id=f"laminar_150lmm_monochromator_{SOLVER}")
+    paths = case.output_paths(SOLVER)
+
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=case.DIFFRACTION_ORDER,
+        fourier_orders=case.QUICK_FOURIER_ORDERS if args.quick else case.FOURIER_ORDERS,
+        show_progress=True,
+        live_plot=args.live_plot,
+        live_plot_x_key="energy_ev",
+        live_plot_order_count=3,
+        on_error="fail_fast",
+        max_workers="auto",
+        resume=False,
+        backend="numba",
+        solver=SOLVER,
+    )
+
+    case.build_grating(quick=args.quick).plot_profile(paths["profile_plot"])
+    results = list(
+        runner.run_cases(
+            case.build_cases(quick=args.quick, stride=args.stride),
+            metadata=case.sweep_metadata(SOLVER),
+        )
+    )
+
+    grax.write_all_orders_csv(results, paths["all_orders_csv"])
+    grax.plot_order_subset(
+        results,
+        paths["orders_plot"],
+        diffraction_orders=case.PLOT_ORDERS,
+        title=f"Laminar 150 l/mm Monochromator Sweep, {SOLVER_TITLE}: Orders 1-3",
+    )
+
+    successful = sum(result.status == "ok" for result in results)
+    print(f"Computed {successful} monochromator points with the {SOLVER} solver.")
+    print(f"All-orders CSV saved to: {paths['all_orders_csv']}")
+    print(f"Orders plot saved to: {paths['orders_plot']}")
+    print(f"Grating profile saved to: {paths['profile_plot']}")
+
+
+# Spawned multiprocessing workers re-import this file by path; without the guard
+# each worker would re-run the whole sweep and recursively spawn more.
+if __name__ == "__main__":
+    main()
diff --git a/validation/laminar_150lmm/run_rcwa.py b/validation/laminar_150lmm/run_rcwa.py
new file mode 100644
index 0000000..1711709
--- /dev/null
+++ b/validation/laminar_150lmm/run_rcwa.py
@@ -0,0 +1,84 @@
+"""Run the laminar 150 l/mm monochromator sweep with the RCWA solver.
+
+Writes ``results/laminar_150lmm_monochromator_all_orders_rcwa.csv`` plus an
+orders 1-3 plot. The grating and the sweep grid come from
+``grating_definition.py``, which ``run_neviere.py`` also uses, so the two runs
+stay comparable.
+
+```bash
+python validation/laminar_150lmm/run_rcwa.py
+python validation/laminar_150lmm/run_rcwa.py --quick
+```
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+parser = argparse.ArgumentParser(description="Laminar 150 l/mm monochromator sweep (RCWA)")
+parser.add_argument("--quick", action="store_true", help="Run a few coarse energy points")
+parser.add_argument("--stride", type=int, default=1, help="Keep every Nth energy point")
+parser.add_argument("--live-plot", action="store_true", help="Show the sweep while it runs")
+args = parser.parse_args()
+
+os.environ.setdefault("MPLBACKEND", "TkAgg" if args.live_plot else "Agg")
+
+import grax  # noqa: E402
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+import grating_definition as case  # noqa: E402
+
+SOLVER = "rcwa"
+SOLVER_TITLE = "RCWA"
+
+
+def main() -> None:
+    """Run the sweep and write this solver's artifacts."""
+
+    grax.setup_logging(level="INFO", run_id=f"laminar_150lmm_monochromator_{SOLVER}")
+    paths = case.output_paths(SOLVER)
+
+    runner = grax.BatchSimulationRunner(
+        diffraction_order=case.DIFFRACTION_ORDER,
+        fourier_orders=case.QUICK_FOURIER_ORDERS if args.quick else case.FOURIER_ORDERS,
+        show_progress=True,
+        live_plot=args.live_plot,
+        live_plot_x_key="energy_ev",
+        live_plot_order_count=3,
+        on_error="fail_fast",
+        max_workers="auto",
+        resume=False,
+        backend="numba",
+        solver=SOLVER,
+    )
+
+    case.build_grating(quick=args.quick).plot_profile(paths["profile_plot"])
+    results = list(
+        runner.run_cases(
+            case.build_cases(quick=args.quick, stride=args.stride),
+            metadata=case.sweep_metadata(SOLVER),
+        )
+    )
+
+    grax.write_all_orders_csv(results, paths["all_orders_csv"])
+    grax.plot_order_subset(
+        results,
+        paths["orders_plot"],
+        diffraction_orders=case.PLOT_ORDERS,
+        title=f"Laminar 150 l/mm Monochromator Sweep, {SOLVER_TITLE}: Orders 1-3",
+    )
+
+    successful = sum(result.status == "ok" for result in results)
+    print(f"Computed {successful} monochromator points with the {SOLVER} solver.")
+    print(f"All-orders CSV saved to: {paths['all_orders_csv']}")
+    print(f"Orders plot saved to: {paths['orders_plot']}")
+    print(f"Grating profile saved to: {paths['profile_plot']}")
+
+
+# Spawned multiprocessing workers re-import this file by path; without the guard
+# each worker would re-run the whole sweep and recursively spawn more.
+if __name__ == "__main__":
+    main()
diff --git a/validation/optimizer/parameter_influence_study.py b/validation/optimizer/parameter_influence_study.py
index d744008..110d1ee 100644
--- a/validation/optimizer/parameter_influence_study.py
+++ b/validation/optimizer/parameter_influence_study.py
@@ -79,8 +79,8 @@
 sweeps_dir.mkdir(parents=True, exist_ok=True)
 all_rows = []
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=15,
+    diffraction_order=1,
+    fourier_orders=15,
     show_progress=True,
     on_error="continue",
     resume=False,
diff --git a/validation/optimizer/run_simulation_design_param.py b/validation/optimizer/run_simulation_design_param.py
index 8352b9e..c2e4416 100644
--- a/validation/optimizer/run_simulation_design_param.py
+++ b/validation/optimizer/run_simulation_design_param.py
@@ -78,8 +78,8 @@
 )
 
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=1,
-    default_fourier_orders=5 if quick_mode else 15,
+    diffraction_order=1,
+    fourier_orders=5 if quick_mode else 15,
     show_progress=True,
     live_plot=LIVE_PLOT,
     live_plot_x_key="energy_ev",
diff --git a/validation/optimizer/run_simulation_fit_laminar_grating.py b/validation/optimizer/run_simulation_fit_laminar_grating.py
index e288ce1..d29e360 100644
--- a/validation/optimizer/run_simulation_fit_laminar_grating.py
+++ b/validation/optimizer/run_simulation_fit_laminar_grating.py
@@ -89,8 +89,8 @@
     cases = (dict(case, label="monochromator") for case in cases)
 
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=diffraction_order,
-    default_fourier_orders=fourier_orders,
+    diffraction_order=diffraction_order,
+    fourier_orders=fourier_orders,
     show_progress=True,
     live_plot=LIVE_PLOT,
     live_plot_x_key="energy_ev",
diff --git a/validation/optimizer/run_simulation_fit_laminar_grating_with_roughness.py b/validation/optimizer/run_simulation_fit_laminar_grating_with_roughness.py
index cc49610..5211880 100644
--- a/validation/optimizer/run_simulation_fit_laminar_grating_with_roughness.py
+++ b/validation/optimizer/run_simulation_fit_laminar_grating_with_roughness.py
@@ -100,8 +100,8 @@
     )
 
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=diffraction_order,
-    default_fourier_orders=fourier_orders,
+    diffraction_order=diffraction_order,
+    fourier_orders=fourier_orders,
     show_progress=True,
     live_plot=LIVE_PLOT,
     live_plot_x_key="energy_ev",
diff --git a/validation/optimizer/run_simulation_fit_laminar_roughness_only.py b/validation/optimizer/run_simulation_fit_laminar_roughness_only.py
index 2c13fda..28fa6d3 100644
--- a/validation/optimizer/run_simulation_fit_laminar_roughness_only.py
+++ b/validation/optimizer/run_simulation_fit_laminar_roughness_only.py
@@ -100,8 +100,8 @@
     )
 
 runner = grax.BatchSimulationRunner(
-    default_diffraction_order=diffraction_order,
-    default_fourier_orders=fourier_orders,
+    diffraction_order=diffraction_order,
+    fourier_orders=fourier_orders,
     show_progress=True,
     live_plot=LIVE_PLOT,
     live_plot_x_key="energy_ev",