Recurrent Machine Learning and Computing with Nonlinear Optical Waves

Ian A. D. Williamson; Tyler W. Hughes; Momchil Minkov; Shanhui Fan

doi:10.1364/CLEO_QELS.2020.FW4B.1

Conference on Lasers and Electro-Optics
OSA Technical Digest (Optica Publishing Group, 2020),
paper FW4B.1
•https://doi.org/10.1364/CLEO_QELS.2020.FW4B.1

Recurrent Machine Learning and Computing with Nonlinear Optical Waves

Ian A. D. Williamson, Tyler W. Hughes, Momchil Minkov, and Shanhui Fan

CLEO: QELS_Fundamental Science 2020

Washington, DC United States
10–15 May 2020
ISBN: 978-1-943580-76-7

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Inverse Design and Computation (FW4B)

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I. A. D. Williamson, T. W. Hughes, M. Minkov, and S. Fan, "Recurrent Machine Learning and Computing with Nonlinear Optical Waves," in Conference on Lasers and Electro-Optics, OSA Technical Digest (Optica Publishing Group, 2020), paper FW4B.1.

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Abstract

We demonstrate that optical time-dynamics are equivalent to a recurrent neural network and that they can be trained for high-performance on complex classification tasks, paving the way for passive analog machine learning processors.

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