Coherent beam combination of fiber lasers based on stochastic parallel gradient descent algorithm

被引:0
|
作者
Long Xuejun [1 ]
Liang Yonghui [1 ]
Xu Xiaojun [1 ]
Wang Sanhong [1 ]
Yu Qifeng [1 ]
机构
[1] Natl Univ Def Technol, Optoelect Sci & Engn Inst, Changsha 410073, Peoples R China
来源
关键词
fiber laser; coherent beam combination; stochastic parallel gradient descent; beam-quality-metric function;
D O I
暂无
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Coherent beam combination of fiber laser arrays plays an important role in realizing high power, high radiance fiber laser systems. The stochastic parallel gradient descent (SPGD) algorithm is a newly developed optimization method using the technique of parallel perturbation and stochastic approximation and it is expected that this algorithm can reduce the cost and complexity of a high power fiber laser system when incorporated in its beam combination scheme. In this paper, a numerical simulation model about the fiber laser beam combination system is then established based on beam-quality-metric optimization method. The SPGD algorithm is introduced and used to realize the beam-quality-metric maximization, leading to the maximum output power of the fiber laser system. The results of numerical simulation indicate that the far-field beam intensity optimization method using SPGD algorithm can realize coherent beam combination of fiber laser arrays effectively.
引用
收藏
页码:U264 / U268
页数:5
相关论文
共 50 条
  • [31] Simulation and Verification of Beam Combination Using a Stochastic Parallel Gradient Descent Algorithm with Energy Feedback Adaptation
    Li, Jianhong
    Gao, Liang
    An, Yan
    Hu, Lichao
    Li, Xiang
    Song, Yansong
    Dong, Keyan
    LASER & OPTOELECTRONICS PROGRESS, 2025, 62 (03)
  • [32] Simulation and analysis of Stochastic Parallel Gradient Descent control algorithm for coherent combining
    Zheng, Yi
    Shen, Feng
    2008 INTERNATIONAL CONFERENCE ON OPTICAL INSTRUMENTS AND TECHNOLOGY: OPTICAL SYSTEMS AND OPTOELECTRONIC INSTRUMENTS, 2009, 7156
  • [33] Bandwidth analysis and improvement of the beam phasing of fiber amplifiers using the stochastic parallel gradient descent algorithm
    Zhou, Pu
    Liu, Zejin
    Ma, Yanxing
    Wang, Xiaolin
    Ma, Haotong
    Xu, Xiaojun
    OPTICS AND LASER TECHNOLOGY, 2010, 42 (07): : 1059 - 1065
  • [34] Adaptive Gradient Estimation Stochastic Parallel Gradient Descent Algorithm for Laser Beam Cleanup
    Ma, Shiqing
    Yang, Ping
    Lai, Boheng
    Su, Chunxuan
    Zhao, Wang
    Yang, Kangjian
    Jin, Ruiyan
    Cheng, Tao
    Xu, Bing
    PHOTONICS, 2021, 8 (05)
  • [35] Fast and accurate modal decomposition of multimode fiber based on stochastic parallel gradient descent algorithm
    Lu, Haibin
    Zhou, Pu
    Wang, Xiaolin
    Jiang, Zongfu
    APPLIED OPTICS, 2013, 52 (12) : 2905 - 2908
  • [36] Wavefront-based stochastic parallel gradient descent beam control
    Belen'kii, Mikhail S.
    Hughes, Kevin
    Runyeon, Hope
    Rye, Vincent
    ADVANCED WAVEFRONT CONTROL: METHODS, DEVICES, AND APPLICATIONS V, 2007, 6711
  • [37] Coregistration based on stochastic parallel gradient descent algorithm for SAR interferometry
    Long, Xuejun
    Fu, Sihua
    Yu, Qifeng
    Wang, Sanhong
    Qi, Bo
    Ren, Ge
    REMOTE SENSING LETTERS, 2014, 5 (11) : 991 - 1000
  • [38] Laser beam shaping based on wavefront sensorless adaptive optics with stochastic parallel gradient descent algorithm
    Li, Yan
    Peng, Tairan
    Li, Wenlai
    Han, Hongming
    Ma, Jianqiang
    14TH NATIONAL CONFERENCE ON LASER TECHNOLOGY AND OPTOELECTRONICS (LTO 2019), 2019, 11170
  • [39] Experimental explorations of the laser beam cleanup system based on stochastic parallel-gradient-descent algorithm
    Liang, Yonghui
    Wang, Sanhong
    Long, Xuejun
    Yu, Qifeng
    Guangxue Xuebao/Acta Optica Sinica, 2008, 28 (04): : 613 - 618
  • [40] Fiber lasers and it's coherent beam combination
    Lou, Qi-Hong
    He, Bing
    Zhou, Jun
    Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering, 2007, 36 (02): : 155 - 159