Deep-learning-empowered synthetic dimension dynamics: morphing of light into topological modes

Shiqi Xia; Sihong Lei; Daohong Song; Luigi Di Lauro; Imtiaz Alamgir; Liqin Tang; Jingjun Xu; Roberto Morandotti; Hrvoje Buljan; Zhigang Chen

doi:10.1117/1.AP.6.2.026005

Advanced Photonics, Volume. 6, Issue 2, 026005(2024)

Deep-learning-empowered synthetic dimension dynamics: morphing of light into topological modes

Shiqi Xia^1、†, Sihong Lei¹, Daohong Song^1,2, Luigi Di Lauro³, Imtiaz Alamgir³, Liqin Tang^1,2, Jingjun Xu¹, Roberto Morandotti³, Hrvoje Buljan^1,4、*, and Zhigang Chen^1,2、*

Author Affiliations

¹Nankai University, TEDA Institute of Applied Physics, School of Physics, The MOE Key Laboratory of Weak-Light Nonlinear Photonics, Tianjin, China

²Shanxi University, Collaborative Innovation Center of Extreme Optics, Taiyuan, China

³INRS-EMT, Varennes, Quebec, Canada

⁴University of Zagreb, Department of Physics, Faculty of Science, Zagreb, Croatia

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Shiqi Xia, Sihong Lei, Daohong Song, Luigi Di Lauro, Imtiaz Alamgir, Liqin Tang, Jingjun Xu, Roberto Morandotti, Hrvoje Buljan, Zhigang Chen. Deep-learning-empowered synthetic dimension dynamics: morphing of light into topological modes[J]. Advanced Photonics, 2024, 6(2): 026005

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Paper Information

Category: Research Articles

Received: Oct. 1, 2023

Accepted: Feb. 20, 2024

Published Online: Mar. 19, 2024

The Author Email: Buljan Hrvoje (hbuljan.phy@pmf.hr), Chen Zhigang (zgchen@nankai.edu.cn)

DOI:10.1117/1.AP.6.2.026005

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology