Chinese Journal of Lasers, Volume. 52, Issue 3, 0301001(2025)

Stabilization of Intelligent Laser Cavity Based on Deep Reinforcement Learning Algorithm

Jingyu Li1,2, Zongzhe Zhang1, Jing Yang1,2、*, Lin Han1,2, Hao Wang1,2, Yunping Wang3, Hongwei Gao1,2, Xiaojun Wang1,2, and Zuyan Xu1
Author Affiliations
  • 1Key Lab of Functional Crystals and Laser Technology, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Beijing Institute of Tracking and Communication Technology, Beijing 100094, China
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    Figures & Tables(11)
    Schematic diagram of composition and principle of agent
    Schematic diagram of laser resonator integrated with intelligent agent
    Impact of different parameters on resonator. (a) Radius of fundamental mode versus thermal focal length; (b) mirror misalignment versus power detuning
    Hierarchical structure diagram of intelligent agent
    Curves of training-reward with different numbers of neurons
    Comparison among intelligent agent, SPGD, and GA under different detuning conditions, with illustration showing two-dimensional distributions of corresponding far-field beam patterns
    Statistical distribution of recovery time in experimental and simulation tests
    Evolution of output power over time in intelligent agent control process, with illustration showing spatial distributions of 3D beam
    Evolution curve of laser output power with time
    Typical M2 measurement result after optimization, with illustration of corresponding far-field two-dimensional beam spatial distribution
    • Table 1. Performance comparison of different algorithms

      View table

      Table 1. Performance comparison of different algorithms

      AlgorithmMean value μStandard deviation σCv /%
      SPGD1100.80639.770.58
      GA1585.00721.130.45
      DRL79.8052.050.65
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    Jingyu Li, Zongzhe Zhang, Jing Yang, Lin Han, Hao Wang, Yunping Wang, Hongwei Gao, Xiaojun Wang, Zuyan Xu. Stabilization of Intelligent Laser Cavity Based on Deep Reinforcement Learning Algorithm[J]. Chinese Journal of Lasers, 2025, 52(3): 0301001

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    Paper Information

    Category: laser devices and laser physics

    Received: Apr. 9, 2024

    Accepted: Jun. 3, 2024

    Published Online: Jan. 14, 2025

    The Author Email: Yang Jing (yangjing@mail.ipc.ac.cn)

    DOI:10.3788/CJL240755

    CSTR:32183.14.CJL240755

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