波前
斯太尔率
光学
自适应光学
波前传感器
变形镜
物理
计算机科学
作者
Xiu-Shan Pan,Heng Zuo,Hua Bai,Zhixu Wu,Xiangqun Cui
出处
期刊:Optics Express
[The Optical Society]
日期:2023-01-03
卷期号:31 (2): 1067-1067
被引量:2
摘要
Real-time wavefront correction is a challenging problem to present for conventional adaptive optics systems. Here, we present an all-optical system to realize real-time wavefront correction. Using deep learning, the system, which contains only multiple transmissive diffractive layers, is trained to realize high-quality imaging for unknown, random, distorted wavefronts. Once physically fabricated, this passive optical system is physically positioned between the imaging lens and the image plane to all-optically correct unknown, new wavefronts whose wavefront errors are within the training range. Simulated experiments showed that the system designed for the on-axis field of view increases the average imaging Strehl Ratio from 0.32 to 0.94, and the other system intended for multiple fields of view increases the resolvable probability of binary stars from 30.5% to 69.5%. Results suggested that DAOS performed well when performing wavefront correction at the speed of light. The solution of real-time wavefront correction can be applied to other wavelengths and has great application potential in astronomical observation, laser communication, and other fields.
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