renjieli08/Photonics-FDTD-DRL
Optimization and inverse design of photonic crystals using deep reinforcement learning
This project helps optical engineers and nanophotonics researchers automate the inverse design of nanoscale laser cavities. It takes optical specifications and uses Deep Reinforcement Learning to output optimized photonic crystal designs, significantly reducing the time and manual effort traditionally required by human experts. The primary users are scientists and engineers working on semiconductor lasers and integrated photonics.
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Use this if you are spending weeks or months manually searching for optimal photonic crystal designs for laser cavities and want to automate this process with AI.
Not ideal if you don't have access to Lumerical FDTD software or existing .fsp simulation files, as these are required to run the inverse design.
Stars
90
Forks
23
Language
Python
License
Apache-2.0
Category
Last pushed
Apr 11, 2023
Commits (30d)
0
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