A universal physics-informed neural network framework for electromagnetic scattering based on quasinormal mode expansion that guarantees compliance with energy conservation and causality and shows improved data efficiency for photonic-crystal slabs and metasurfaces.
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2025 1verdicts
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A general framework for knowledge integration in machine learning for electromagnetic scattering using quasinormal modes
A universal physics-informed neural network framework for electromagnetic scattering based on quasinormal mode expansion that guarantees compliance with energy conservation and causality and shows improved data efficiency for photonic-crystal slabs and metasurfaces.