Blaze2D
Blaze2D computes photonic bands and projected Maxwell operators for two-dimensional periodic dielectric structures. It supports TE and TM polarization, circle geometries, positive scalar permittivity, and square, triangular, rectangular, or explicit oblique lattices. Independent configurations can run in parallel as ordered parameter studies.
The Rust solver is available through Python, a command-line interface, and the browser Workbench. Each uses the same versioned configuration, numerical defaults, coordinate conventions, and result names. Native calculations support f32 or f64 storage; the browser uses f64. Three-dimensional computation, general geometry, and an MPB compatibility adapter are future work.
Install
python -m pip install blaze2d
The package requires CPython 3.10 or later and NumPy. Release wheels cover Linux x86_64, macOS x86_64 and arm64, and Windows x86_64. Plotting and terminal progress are optional:
python -m pip install 'blaze2d[plot,progress]'
Calculate bands
import blaze
result = blaze.solve(
lattice_type="square",
epsilon_background=1.0,
epsilon_atoms=8.9,
radius_atom=0.20,
polarization="TM",
resolution=32,
n_bands=8,
)
frequencies = result["frequencies"] # NumPy: (k_point, band)
print(frequencies.shape)
print(result["metadata"]["build"])
Results are ordinary dictionaries containing named NumPy arrays and scientific metadata. Frequencies use the common reference length recorded in that metadata. Arrays use C ordering; complex outputs have dtype complex128. Eigenvectors are retained only when requested. The solver stopping flag reports eigenvalue stabilization; operator results also include freshly evaluated residuals and orthogonality information.
Run a TOML study
Download an executable example or export a configuration from the Workbench, then run:
blaze2d config validate calculation.toml
blaze2d run calculation.toml --output results.npz
The same study is available in Python:
config = blaze.Config.from_file("calculation.toml")
study = blaze.run(config, threads=4)
for result in study["results"]:
print(result["job_index"])
blaze.save(study, "results.npz")
restored = blaze.load("results.npz")
Use blaze.stream(config) when results should be consumed incrementally. Studies retain completed results and report failures explicitly. JSON, NDJSON, and NPZ exports preserve array shapes, complex values, calculation settings, and build provenance without pickle.
See the API and TOML reference for named sweep axes, registry studies, k-stencils, projected operators, external dielectric data, and checkpoints. Version 0.7 uses schema = "blaze2d/1"; earlier configuration dialects require migration.
Scientific context and benchmark conditions are documented in the technical report and manuscript. MPB also exposes fields, eigenvectors, and group velocities. Blaze focuses on integrated parameter studies and projected operator and derivative extraction.
Source code · Workbench guide · MIT license
1 maintainer
Metadata
1 maintainer
Release files for blaze2d 0.7.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| blaze2d-0.7.0.tar.gz | 277.4 kB | Details |
Built distributions (wheels)
Total release size: 61.9 MB
Release files / blaze2d-0.7.0.tar.gz
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twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / blaze2d-0.7.0-cp310-cp310-macosx_11_0_x86_64.whl
| Download URL | blaze2d-0.7.0-cp310-cp310-macosx_11_0_x86_64.whl |
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| Size | 3.1 MB |
| Tags | CPython 3.10 macOS 11.0+ x86-64 |
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SHA-256 checksum How to use checksums |
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Transparency logRelease files / blaze2d-0.7.0-cp310-cp310-macosx_11_0_arm64.whl
| Download URL | blaze2d-0.7.0-cp310-cp310-macosx_11_0_arm64.whl |
|---|---|
| Size | 2.4 MB |
| Tags | CPython 3.10 macOS 11.0+ ARM64 |
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SHA-256 checksum How to use checksums |
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twine/7.0.0 CPython/3.13.14
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