scholarly journals Wide-Field Telescope Alignment Using the Model-Based Method Combined with the Stochastic Parallel Gradient Descent Algorithm

Photonics ◽  
2021 ◽  
Vol 8 (11) ◽  
pp. 463
Author(s):  
Min Li ◽  
Ang Zhang ◽  
Junbo Zhang ◽  
Hao Xian

To acquire images with higher accuracy of wide-field telescopes, deformable mirrors with more than 100 actuators are used, making the telescope alignment more complex and time-consuming. Furthermore, the position of the obscuration caused by the secondary mirror in the experiment system is changed with the difference of fields of view, making the response matrix of the deformable mirror different in various fields of view. To solve this problem, transfer functions corresponding to different fields of view are calculated according to the wavefront edge check and boundary conditions. In this paper, a model-based method combined with the stochastic parallel gradient descent (SPGD) algorithm is used. The experiment results show that our method can correct the aberrations with a high accuracy in both on-axis and off-axis fields, indicating that the effective actuators are well chosen corresponding to different fields of view.

Photonics ◽  
2021 ◽  
Vol 8 (5) ◽  
pp. 165
Author(s):  
Shiqing Ma ◽  
Ping Yang ◽  
Boheng Lai ◽  
Chunxuan Su ◽  
Wang Zhao ◽  
...  

For a high-power slab solid-state laser, obtaining high output power and high output beam quality are the most important indicators. Adaptive optics systems can significantly improve beam qualities by compensating for the phase distortions of the laser beams. In this paper, we developed an improved algorithm called Adaptive Gradient Estimation Stochastic Parallel Gradient Descent (AGESPGD) algorithm for beam cleanup of a solid-state laser. A second-order gradient of the search point was introduced to modify the gradient estimation, and it was introduced with the adaptive gain coefficient method into the classical Stochastic Parallel Gradient Descent (SPGD) algorithm. The improved algorithm accelerates the search for convergence and prevents it from falling into a local extremum. Simulation and experimental results show that this method reduces the number of iterations by 40%, and the algorithm stability is also improved compared with the original SPGD method.


2009 ◽  
Vol 29 (2) ◽  
pp. 431-436 ◽  
Author(s):  
周朴 Zhou Pu ◽  
刘泽金 Liu Zejin ◽  
马阎星 Ma Yanxing ◽  
王小林 Wang Xiaolin ◽  
许晓军 Xu Xiaojun ◽  
...  

2010 ◽  
Vol 30 (10) ◽  
pp. 2874-2878
Author(s):  
王小林 Wang Xiaolin ◽  
周朴 Zhou Pu ◽  
马阎星 Ma Yanxing ◽  
马浩统 Ma Haotong ◽  
许晓军 Xu Xiaojun ◽  
...  

2009 ◽  
Vol 36 (5) ◽  
pp. 1091-1096
Author(s):  
王三宏 Wang Sanhong ◽  
梁永辉 Liang Yonghui ◽  
龙学军 Long Xuejun ◽  
于起峰 Yu Qifeng ◽  
谢文科 Xie Wenke

2015 ◽  
Vol 42 (4) ◽  
pp. 0402004 ◽  
Author(s):  
黄智蒙 Huang Zhimeng ◽  
唐选 Tang Xuan ◽  
刘仓理 Liu Cangli ◽  
李剑峰 Li Jianfeng ◽  
张大勇 Zhang Dayong ◽  
...  

2014 ◽  
Vol 7 (2) ◽  
pp. 260-266
Author(s):  
刘磊 LIU Lei ◽  
郭劲 GUO Jin ◽  
赵帅 ZHAO Shuai ◽  
姜振华 JIANG Zhen-hua ◽  
孙涛 SUN Tao ◽  
...  

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