Deep-learning-based recognition of multi-singularity structured light

Abstract: Structured light with customized topological patterns inspires diverse classical and quantum investigations underpinned by accurate detection techniques. However, the current detection schemes are limited to vortex beams with a simple phase singularity. The precise recognition of general structured light with multiple singularities remains elusive. Here, we report deep learning (DL) framework that can unveil multi-singularity phase structures in an end-to-end manner, after feeding only two intensity patterns upon beam propagation. By outputting the phase directly, rich and intuitive information of twisted photons is unleashed. The DL toolbox can also acquire phases of Laguerre–Gaussian (LG) modes with a single singularity and other general phase objects likewise. Enabled by this DL platform, a phase-based optical secret sharing (OSS) protocol is proposed, which is based on a more general class of multi-singularity modes than conventional LG beams. The OSS protocol features strong security, wealthy state space, and convenient intensity-based measurements. This study opens new avenues for large-capacity communications, laser mode analysis, microscopy, Bose–Einstein condensates characterization, etc.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Deep-learning-based recognition of multi-singularity structured light ; volume:11 ; number:4 ; year:2021 ; pages:779-786 ; extent:08
Nanophotonics ; 11, Heft 4 (2021), 779-786 (gesamt 08)

Creator
Wang, Hao
Yang, Xilin
Liu, Zeqi
Pan, Jing
Meng, Yuan
Shi, Zijian
Wan, Zhensong
Zhang, Hengkang
Shen, Yijie
Fu, Xing
Liu, Qiang

DOI
10.1515/nanoph-2021-0489
URN
urn:nbn:de:101:1-2022120813203722969235
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:21 AM CEST

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Associated

  • Wang, Hao
  • Yang, Xilin
  • Liu, Zeqi
  • Pan, Jing
  • Meng, Yuan
  • Shi, Zijian
  • Wan, Zhensong
  • Zhang, Hengkang
  • Shen, Yijie
  • Fu, Xing
  • Liu, Qiang

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