Theoretical Proposal of Optical Neural Network Architecture with Temporal Synthetic Dimension

Bo Peng; Shuo Yan; Dali Cheng; Danying Yu; Zhanwei Liu; Vladislav V. Yakovlev; Xianfeng Chen; Luqi Yuan

doi:10.1364/CLEO_QELS.2022.FTh1A.1

Conference on Lasers and Electro-Optics
Technical Digest Series (Optica Publishing Group, 2022),
paper FTh1A.1
•https://doi.org/10.1364/CLEO_QELS.2022.FTh1A.1

Theoretical Proposal of Optical Neural Network Architecture with Temporal Synthetic Dimension

Bo Peng, Shuo Yan, Dali Cheng, Danying Yu, Zhanwei Liu, Vladislav V. Yakovlev, Xianfeng Chen, and Luqi Yuan

CLEO: QELS_Fundamental Science 2022

San Jose, California United States
15–20 May 2022
ISBN: 978-1-957171-05-0

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Virtual: Synthetic Dimensions and Optical/Photonic Simulators and Devices (FTh1A)

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B. Peng, S. Yan, D. Cheng, D. Yu, Z. Liu, V. V. Yakovlev, X. Chen, and L. Yuan, "Theoretical Proposal of Optical Neural Network Architecture with Temporal Synthetic Dimension," in Conference on Lasers and Electro-Optics, Technical Digest Series (Optica Publishing Group, 2022), paper FTh1A.1.

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Abstract

We theoretically propose the construction of the optical neural network architecture for deep learning in a single ring resonator, with the concept of temporal synthetic dimension formed by arrival times of optical pulses.

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