Advanced Photonics, Volume. 4, Issue 6, 064002(2022)

Computation at the speed of light: metamaterials for all-optical calculations and neural networks

Trevon Badloe1、†, Seokho Lee1, and Junsuk Rho1,2,3、*
Author Affiliations
  • 1Pohang University of Science and Technology, Department of Mechanical Engineering, Pohang, Republic of Korea
  • 2Pohang University of Science and Technology, Department of Chemical Engineering, Pohang, Republic of Korea
  • 3POSCO-POSTECH-RIST Convergence Research Center for Flat Optics and Metaphotonics, Pohang, Republic of Korea
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    [117] C. M. Bishop. Pattern Recognition and Machine Learning(2006).

    [120] J. W. Goodman. Introduction to Fourier Optics(2004).

    [141] H. Wei et al. All-optical machine learning using diffractive deep neural networks. Science, 361, 1004-1008(2018).

    [142] T. Wang et al. Image sensing with multilayer, nonlinear optical neural networks(2022).

    [160] I. A. D. Williamson et al. Tunable nonlinear activation functions for optical neural networks, SM1E.2(2020).

    [187] J. Kim et al. Scalably manufactured high-index atomic layer-polymer hybrid metasurfaces for high-efficiency virtual reality metaoptics in the visible(2022).

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    Trevon Badloe, Seokho Lee, Junsuk Rho. Computation at the speed of light: metamaterials for all-optical calculations and neural networks[J]. Advanced Photonics, 2022, 4(6): 064002

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    Paper Information

    Category: Reviews

    Received: Oct. 18, 2022

    Accepted: Nov. 29, 2022

    Posted: Nov. 29, 2022

    Published Online: Dec. 23, 2022

    The Author Email: Rho Junsuk (jsrho@postech.ac.kr)

    DOI:10.1117/1.AP.4.6.064002

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