Experimental Demonstration of an Optical Neural PDE Solver via On-Chip PINN Training
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Abstract (arXiv)
Partial differential equation (PDE) is an important math tool in science and engineering. This paper experimentally demonstrates an optical neural PDE solver by leveraging the back-propagation-free on-photonic-chip training of physics-informed neural networks.
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References · 5
- 2020DeepReach: A Deep Learning Approach to High-Dimensional Reachabilitycited by 81
- 2022Experimentally realized in situ backpropagation for deep learning in nanophotonic neural networkscited by 43
- 2023Tensor-Compressed Back-Propagation-Free Training for (Physics-Informed) Neural Networkscited by 12
- 2022TT-PINN: A Tensor-Compressed Neural PDE Solver for Edge Computingcited by 6
- 2023Real-Time FJ/MAC PDE Solvers via Tensorized, Back-Propagation-Free Optical PINN Trainingcited by 4
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