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BEAMZ

BEAMZ is an electromagnetic simulation package for photonic chip designers using the FDTD method written in Jax. It features a high-level API for fast prototyping with just a few lines of code, an inverse design module for gradient-based optimization using the adjoint method with autodiff.

pip install beamz

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Core Features

  • 100% Python, free (MIT license) & open-source.
  • Modular architecture with a high-level API.
  • GPU-accelerated (but CPU-capable).
  • Built-in layout flow (GDSII import/export).
  • FDTD simulation in 2D and 3D.
  • PML, CPML (WIP), and PEC boundaries.
  • Sub-pixel smoothing (using super-sampling).
  • Gaussian and mode sources with TE and TM polarization.
  • Custom source time profiles.
  • DFT monitors and S-parameter extraction workflow for compact modeling.
  • Streamlined parametric design module and interactive 3D web-view.
  • Optimization/autodiff utilities for gradient-based inverse-design with Jax.

Examples

Read and try out our example notebooks or download and run examples/ from this repository.

About

BEAMZ's goal is to become the pragmatic FDTD engine of choice for photonic chip designers.

It focuses on streamlined workflows to produce useful results without tedious setup or configuration files. While currently still experimental, this is not a research project with the goal to demo a novel framework we can publish, nor a costly, closed API that hides how it works and gives you no ownership. A modular architecture is chosen over a purely object-oriented architecture to make the code readable and development easy so that, if there is something that isn't working or missing, you can quickly add it yourself.

If any of this excites you or if have any questions, please open an issue on GitHub. Feel free to fork this project, to suggest or contribute new features, or simply support the project by giving this repo a star. Thank you!

About

GPU-accelerated electromagnetic FDTD simulations for compact modeling and inverse design / gradient-based optimization of nanophotonic devices with Python.

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