High Power Laser Science and Engineering, Volume. 13, Issue 2, 02000e19(2025)

Deep learning enabled robust wavefront sensing for active beam smoothing with a continuous phase modulator

Yamin Zheng1,2,3, Yifan Zhang1,2,3, Liquan Guo1,2,3, Pei Li1,2,3, Zichao Wang1,2,3, Yongchen Zhuang1,2,3, Shibing Lin1,2,3, Qiao Xue4, Deen Wang4、*, and Lei Huang1,2,3、*
Author Affiliations
  • 1Department of Precision Instrument, Tsinghua University, Beijing, China
  • 2State Key Laboratory of Precision Space-time Information Sensing Technology, Beijing, China
  • 3Key Laboratory of Photonic Control Technology (Tsinghua University), Ministry of Education, Beijing, China
  • 4Research Center of Laser Fusion, China Academy of Engineering Physics (CAEP), Mianyang, China
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    Figures & Tables(9)
    The CPM process in layer systems. (a) CPM optical path. (b) Phase pattern of the CPM. (c) Beam profiles with the CPM and wavefront distortion (DIS). (d) FOPAI curves with the CPM and DIS.
    Principle of the DLWS method and network structure of the SD-Net. The input of the SD-Net is the raw gray-scale map of the spot array and the output is the slope of each individual sub-aperture.
    Slope calculation results using the DLWS method and SHWFS. (a) Beam profile with wavefront distortion (DIS). (b) Spot array and the enlarged area with DIS. (c) DIS. (d) Slopes calculated by the SHWFS. (e) Slopes calculated by the DLWS method. (f) Slope error in the X direction. (g) Slope error in the Y direction.
    Wavefront reconstruction results using the DLWS method and SHWFS. (a) Wavefront reconstructed by the SHWFS. (b) Wavefront reconstruction error of the SHWFS. (c) Wavefront reconstructed by the DLWS method. (d) Wavefront reconstruction error of the DLWS method.
    Experiment configuration of the DLWS method. CPM, continuous phase modulator; RM, reflecting mirror; SHWFS, Shack–Hartmann wavefront sensor; CCD, charge-coupled device; DM, deformable mirror.
    Wavefront results using the DLWS method and SHWFS in the experiment. (a) Spot array. (b), (c) Spots in local sub-apertures. (d) Wavefront reconstruction error of the SHWFS. (e) Wavefront reconstruction error of the DLWS method.
    RMS value of reconstruction errors using the DLWS method and SHWFS in the experiment. (a) RMS of slope reconstruction errors. (b) RMS of wavefront reconstruction errors.
    Wavefront correction results using the DLWS method and SHWFS. (a) Initial wavefront distortion and beam profile. (b) Wavefront reconstruction error and beam profile of the SHWFS. (c) Wavefront reconstruction error and beam profile of the DLWS method. (d) FOPAI curves. (e) Key parameters of FOPAI.
    FOPAI results of beam profiles after wavefront correction based on the DLWS method and the SHWFS.
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    Yamin Zheng, Yifan Zhang, Liquan Guo, Pei Li, Zichao Wang, Yongchen Zhuang, Shibing Lin, Qiao Xue, Deen Wang, Lei Huang. Deep learning enabled robust wavefront sensing for active beam smoothing with a continuous phase modulator[J]. High Power Laser Science and Engineering, 2025, 13(2): 02000e19

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    Paper Information

    Category: Research Articles

    Received: Sep. 19, 2024

    Accepted: Jan. 14, 2025

    Published Online: Apr. 18, 2025

    The Author Email: Deen Wang (sduwde@126.com), Lei Huang (hl@tsinghua.edu.cn)

    DOI:10.1017/hpl.2025.6

    CSTR:32185.14.hpl.2025.6

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