Mr. Zhenheng Xu Profile

Zhenheng Xu

at Huazhong Univ of Science and Technology

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Proceedings Article | 8 November 2018 Paper

Optimization algorithms for wavefront sensorless adaptive optics

Xueting Wu, Xiuhua Yuan, Zhenheng Xu

Proceedings Volume 10817, 108170L (2018) https://doi.org/10.1117/12.2500527

KEYWORDS: Genetic algorithms, Adaptive optics, Wavefronts, Optimization (mathematics), Zernike polynomials, Wavefront distortions, Computer simulations, Distortion, Fourier transforms, Sensors

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The acquisition of phase information of light field is the key technology of adaptive optics. Using intensity of the light field to derive the phase distribution of the light field has become a common application technique for phase recovery. Research shows that iterative algorithm is an effective method for phase recovery of light field, but some iterative algorithms have the disadvantages of being sensitive to initial values, easy to fall into local extremum and slow convergence. Here we mainly focus on two iterative optimization algorithms for wavefront distortion correction without wavefront sensing adaptive optics. The first is the Gerchberg-Saxton (GS) algorithm, which combines two complex amplitude distributions on the plane of the optical propagation perpendicular to the optical axis and recovers the phase from the intensity distribution. The second is a genetic algorithm that achieves an optimal solution for the evaluation function through a series of hybridization, mutation, and selection operations. In order to improve its convergence rate, we take Zernike polynomial coefficient required for wavefront reconstruction as the optimization object instead of voltages on corrector traditionally. We numerically simulate the performance of two algorithms, use Zernike polynomial to fit the static aberration, and study a series of parameters, especially single-order aberrations and random multi-order aberrations as the initial phase to the correction effect, and the correction performance of the two algorithms is respectively evaluated using two evaluation functions, Sum-Square Error (SSE) and Strehl Ratio (SR). Time consumption is also mentioned to evaluate the performance of two algorithms.

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