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Photonics Research, Volume. 9, Issue 3, B71(2021)

Backpropagation through nonlinear units for the all-optical training of neural networks

Xianxin Guo1,2,3,5、†,*, Thomas D. Barrett2,6、†,*, Zhiming M. Wang1,7、*, and A. I. Lvovsky2,4,8、*
Author Affiliations
  • 1Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China
  • 2Clarendon Laboratory, University of Oxford, Oxford OX1 3PU, UK
  • 3Institute for Quantum Science and Technology, University of Calgary, Calgary, Alberta T2N 1N4, Canada
  • 4Russian Quantum Center, Skolkovo 143025, Moscow, Russia
  • 5e-mail: xianxin.guo@physics.ox.ac.uk
  • 6e-mail: thomas.barrett@physics.ox.ac.uk
  • 7e-mail: zhmwang@uestc.edu.cn
  • 8e-mail: alex.lvovsky@physics.ox.ac.uk
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    CLP Journals

    [1] Li Gao, Yang Chai, Darko Zibar, Zongfu Yu, "Deep learning in photonics: introduction," Photonics Res. 9, DLP1 (2021)

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    Xianxin Guo, Thomas D. Barrett, Zhiming M. Wang, A. I. Lvovsky, "Backpropagation through nonlinear units for the all-optical training of neural networks," Photonics Res. 9, B71 (2021)

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    Paper Information

    Special Issue: DEEP LEARNING IN PHOTONICS

    Received: Oct. 8, 2020

    Accepted: Jan. 11, 2021

    Published Online: Mar. 2, 2021

    The Author Email: Xianxin Guo (xianxin.guo@physics.ox.ac.uk), Thomas D. Barrett (thomas.barrett@physics.ox.ac.uk), Zhiming M. Wang (zhmwang@uestc.edu.cn), A. I. Lvovsky (alex.lvovsky@physics.ox.ac.uk)

    DOI:10.1364/PRJ.411104

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology