A PyTorch Library for Photonic AI Computing Model Training and Co-Design (NeurIPS'21)
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Updated
Jan 13, 2026 - Python
A PyTorch Library for Photonic AI Computing Model Training and Co-Design (NeurIPS'21)
optical attention via wave interference in holographic crystals verified to float precision. the math is done. contribute to build the hardware.star it, fork it, break it.
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This repository contains the supplementary package accompanying the manuscript: Photonic Mixture-of-Experts for scalable on-chip multi-task optical neural networks
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Public research archive for programmable photonic computing, mixed-signal survivability, and resident sparse-decision processing.
Official pytorch implementation of the paper: "Illumination Angular Spectrum Encoding for Controlling the Functionality of Diffractive Networks"
This repository accompanies “Free-Space Coherent Optical Dot-Product Multiplier with Lensless Fan-In” (Duque et al., 2026). It provides simulation code for a coherent free-space optical dot-product system using DMD/SLM-style modulation and camera-like readout.
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Transparent benchmark cards, JSON artifacts, and visual tools for photonic AI accelerator energy/noise claims.
Simulation-only validation ladder for mapping neural weight matrices to HRM-style photonic transfer functions.
An idea, a set of equations, and a body of simulation code — shared openly > because I believe it deserves to be checked by people who have the lab > equipment I don't
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