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  • Title: Fast High-Resolution Phase Diversity Wavefront Sensing with L-BFGS Algorithm.
    Author: Zhang H, Ju G, Guo L, Xu B, Bai X, Jiang F, Xu S.
    Journal: Sensors (Basel); 2023 May 22; 23(10):. PubMed ID: 37430879.
    Abstract:
    The presence of manufacture error in large mirrors introduces high-order aberrations, which can severely influence the intensity distribution of point spread function. Therefore, high-resolution phase diversity wavefront sensing is usually needed. However, high-resolution phase diversity wavefront sensing is restricted with the problem of low efficiency and stagnation. This paper proposes a fast high-resolution phase diversity method with limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, which can accurately detect aberrations in the presence of high-order aberrations. An analytical gradient of the objective function for phase-diversity is integrated into the framework of the L-BFGS nonlinear optimization algorithm. L-BFGS algorithm is specifically suitable for high-resolution wavefront sensing where a large phase matrix is optimized. The performance of phase diversity with L-BFGS is compared to other iterative method through simulations and a real experiment. This work contributes to fast high-resolution image-based wavefront sensing with a high robustness.
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