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Deep nonlinear optical neural networks using physics-aware training

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Abstract

We experimentally demonstrate deep nonlinear optical neural networks using a universal algorithm for backpropagating through arbitrary physical input-output transformations. Ultrafast second harmonic generation and other diverse processes are trained to perform image and audio classification.

© 2021 The Author(s)

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More Like This
Deep nonlinear optical neural networks trained with in situ backpropagation

Logan G. Wright, Tatsuhiro Onodera, Martin M. Stein, Tianyu Wang, Darren T. Schachter, Zoey Hu, and Peter L. McMahon
NTh1A.6 Nonlinear Optics (NLO) 2021

Deep Physical Neural Networks based on Ultrafast Nonlinear Optics

Logan G. Wright, Tatsuhiro Onodera, Martin M. Stein, Tianyu Wang, Darren T. Schachter, Zoey Hu, and Peter L. McMahon
NpM3G.4 Nonlinear Photonics (NP) 2022

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Logan G. Wright, Tatsuhiro Onodera, Martin M. Stein, Tianyu Wang, Darren T. Schachter, Zoey Hu, and Peter L. McMahon
SF4F.1 CLEO: Science and Innovations (CLEO_SI) 2022

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