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#photonics

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papersSEP 11 04:00 UTC

Physics-constrained neural networks speed up RCWA surrogate modeling of periodic structures

A new arXiv paper presents a physics-constrained neural network that predicts rigorous coupled-wave analysis outputs directly as Jones matrices for lossless layered periodic structures. The approach builds on energy conservation to constrain the model, aiming to replace or accelerate conventional simulations that are computationally expensive. The work falls under machine learning for scientific computing and photonics design.

physics-informed/neural-networks/surrogate-modeling/photonics