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12 August 2023 Optical design using physics-inspired neural networks
Demetri Psaltis, Carlo Gigli, Amirhossein Saba
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Proceedings Volume PC12622, Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VI; PC126220I (2023) https://doi.org/10.1117/12.2679815
Event: SPIE Optical Metrology, 2023, Munich, Germany
Abstract
We will describe MaxwellNet, a machine learning method for analyzing and designing optical systems using Maxwell's equations as the loss function in the optimisation process. We will describe results of the application of MaxwellNet to nanophotonics, nonlinear optics and optical diffraction tomography
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Demetri Psaltis, Carlo Gigli, and Amirhossein Saba "Optical design using physics-inspired neural networks", Proc. SPIE PC12622, Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VI, PC126220I (12 August 2023); https://doi.org/10.1117/12.2679815
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KEYWORDS
Optical design
Neural networks
Physics
Nonlinear optics
Diffraction
Machine learning
Maxwell equations
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