Polarization diffractive networks: performing multiple linear transformations using a polarization-encoded diffractive optical network

Jingxi Li; Yi-Chun Hung; Onur Kulce; Deniz Mengu; Aydogan Ozcan

doi:10.1117/12.2648156

17 March 2023 Polarization diffractive networks: performing multiple linear transformations using a polarization-encoded diffractive optical network

Jingxi Li, Yi-Chun Hung, Onur Kulce, Deniz Mengu, Aydogan Ozcan

Author Affiliations +

Proceedings Volume PC12438, AI and Optical Data Sciences IV; PC1243807 (2023) https://doi.org/10.1117/12.2648156
Event: SPIE OPTO, 2023, San Francisco, California, United States

Abstract

We report a polarization-encoded diffractive network to perform multiple arbitrary complex-valued linear transforms within a single diffractive processor. An array of pre-selected linear polarizers is placed between the trainable isotropic diffractive layers, and distinct complex-valued linear transformations are individually assigned to different combinations of input/output polarization states. A polarization-encoded diffractive network performs the target linear transforms with negligible error when N ≥ P x I x O, where N is the number of trainable diffractive features/neurons, I and O denote the number of pixels at the input and output fields-of-view, respectively, and P represents the number of target linear transforms.

Conference Presentation

Citation Download Citation

Jingxi Li, Yi-Chun Hung, Onur Kulce, Deniz Mengu, and Aydogan Ozcan "Polarization diffractive networks: performing multiple linear transformations using a polarization-encoded diffractive optical network", Proc. SPIE PC12438, AI and Optical Data Sciences IV, PC1243807 (17 March 2023); https://doi.org/10.1117/12.2648156

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