Chinese Optics Letters, Volume. 22, Issue 11, (2024)

Experiment validation for high-order vector-eigenmode decomposition with polarization characteristics [Early Posting]

Zhao Huihui, Wang Siyan, Huang Yancheng, Chen Wei, Pang Fufei, Zeng Xianglong
Author Affiliations
  • Shanghai University
  • show less

    Vector vortex beams (VVBs) have attracted considerable attention due to their unique polarization distribution and helical phase wavefront. We first attempt to retrieve the modal coefficients of hybrid VVBs measured by their multiplex polarized intensities through deep learning (DL)-based Stochastic parallel gradient descent (SPGD) algorithm. Xception-based DL model with multi-view images can successfully make an accurate prediction of modal coefficients validated by theoretical calculations of the waveplate angles, demonstrating a high correlation of up to 99.65%. The universality of the DL-SPGD algorithm to high-order vector-eigenmodes (VMs) decomposition is proven to enable the precise reconstruction of modal patterns generated by all-fiber mode-selective couplers in the form of VM and orbital angular momentum (OAM) mode bases, which greatly promotes the accurate characteristics of VVBs in laser beam characterization and fiber mode-division multiplexing.

    Paper Information

    Manuscript Accepted: May. 16, 2024

    Posted: Jun. 11, 2024

    DOI: 10.3788/COL202422.110602