Transformation and phase retrieval of electromagnetic fields between a plane and an arbitrary surface using machine learning

Barak Hadad; Sahar Froim; Amit Bekerman; Yakir Hadad; Alon Bahabad

doi:10.1117/12.2647697

17 March 2023 Transformation and phase retrieval of electromagnetic fields between a plane and an arbitrary surface using machine learning

Barak Hadad, Sahar Froim, Amit Bekerman, Yakir Hadad, Alon Bahabad

Author Affiliations +

Proceedings Volume PC12438, AI and Optical Data Sciences IV; PC124380O (2023) https://doi.org/10.1117/12.2647697
Event: SPIE OPTO, 2023, San Francisco, California, United States

Abstract

The ability to tailor a specific electromagnetic field pattern along an arbitrary selected surface is interesting and of substantial importance considering its numerous immediate applications. It belongs to a class of inverse source problems, and as such it is challenging when only partial data is given. Here, a deep learning-based method that can map the electromagnetic field from an arbitrarily selected surface to a flat surface is presented. In addition, phase retrieval capability is demonstrated for finding both the phase and amplitude on an input flat surface from knowing only the amplitude on an arbitrarily selected surface.

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Citation Download Citation

Barak Hadad, Sahar Froim, Amit Bekerman, Yakir Hadad, and Alon Bahabad "Transformation and phase retrieval of electromagnetic fields between a plane and an arbitrary surface using machine learning", Proc. SPIE PC12438, AI and Optical Data Sciences IV, PC124380O (17 March 2023); https://doi.org/10.1117/12.2647697

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