Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Sensors (Basel). 2023 May 22;23(10):4966. doi: 10.3390/s23104966.
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.
大镜子制造误差的存在会引入高阶像差,这会严重影响点扩散函数的强度分布。因此,通常需要高分辨率的相位差波前传感。然而,高分辨率相位差波前传感受到低效率和停滞问题的限制。本文提出了一种基于有限记忆的 Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) 算法的快速高分辨率相位差方法,该方法可以在存在高阶像差的情况下准确地检测像差。将相位差的目标函数的解析梯度集成到 L-BFGS 非线性优化算法的框架中。L-BFGS 算法特别适用于需要优化大相位矩阵的高分辨率波前传感。通过模拟和实际实验,将 L-BFGS 的相位差性能与其他迭代方法进行了比较。这项工作有助于实现具有高鲁棒性的快速高分辨率基于图像的波前传感。