Deep learning-assisted mode control in synthetic dimension

Shiqi Xia; Sihong Lei; Liqin Tang; Daohong Song; Zhigang Chen

doi:10.1364/FIO.2022.JTu5B.36

Frontiers in Optics + Laser Science 2022 (FIO, LS)
Technical Digest Series (Optica Publishing Group, 2022),
paper JTu5B.36
•https://doi.org/10.1364/FIO.2022.JTu5B.36

Deep learning-assisted mode control in synthetic dimension

Shiqi Xia, Sihong Lei, Liqin Tang, Daohong Song, and Zhigang Chen

Laser Science 2022

Rochester, New York United States
17–20 October 2022
ISBN: 978-1-957171-17-3

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Joint Poster Session IIB (Remote) (JTu5B)

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S. Xia, S. Lei, L. Tang, D. Song, and Z. Chen, "Deep learning-assisted mode control in synthetic dimension," in Frontiers in Optics + Laser Science 2022 (FIO, LS), Technical Digest Series (Optica Publishing Group, 2022), paper JTu5B.36.

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Abstract

We design synthetic modal dimension (SMD) by deep learning and demonstrate direct mode control in such SMD through engineered photonic lattices, including mode confinement and conversion which are otherwise difficult to achieve in real-space dimensions.

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