All-Optical Computation of an Arbitrary Linear Transform Using Diffractive Networks

Onur Kulce; Onur Kulce; Onur Kulce; Deniz Mengu; Deniz Mengu; Deniz Mengu; Yair Rivenson; Yair Rivenson; Yair Rivenson; Aydogan Ozcan; Aydogan Ozcan; Aydogan Ozcan

doi:10.1364/COSI.2022.CTu3F.4

Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)
Technical Digest Series (Optica Publishing Group, 2022),
paper CTu3F.4
•https://doi.org/10.1364/COSI.2022.CTu3F.4

All-Optical Computation of an Arbitrary Linear Transform Using Diffractive Networks

Onur Kulce, Deniz Mengu, Yair Rivenson, and Aydogan Ozcan

Computational Optical Sensing and Imaging 2022

Vancouver, British Columbia Canada
11–15 July 2022
ISBN: 978-1-957171-09-8

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Optical Computing and Phase Retrieval (CTu3F)

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O. Kulce, D. Mengu, Y. Rivenson, and A. Ozcan, "All-Optical Computation of an Arbitrary Linear Transform Using Diffractive Networks," in Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP), Technical Digest Series (Optica Publishing Group, 2022), paper CTu3F.4.

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Abstract

We show that an arbitrary complex-valued linear transform can be performed all-optically using diffractive neural networks that are trained using deep learning.

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