High accuracy deep learning wavefront sensing under high-order turbulence

doi:10.61977/ati2024052

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	High accuracy deep learning wavefront sensing under high-order turbulence
	Liu DM(刘冬明)1,2 ; Liu H(刘辉)1 ; Jin ZY(金振宇)1
发表期刊	天文技术与仪器(英文)/Astronomical Techniques and Instruments
	2024-11
卷号	1 期号:06 页码:316-324
DOI	10.61977/ati2024052
分类号	P111 ; P111.44
产权排序	第1完成单位
收录类别	CSCD
摘要	We explore an end-to-end wavefront sensing approach based on deep learning, which aims to deal with the high-order turbulence and the discontinuous aberration caused by optical system obstructions commonly encountered in real-world ground-based telescope observations. We have considered factors such as the entrance pupil wavefront containing high-order turbulence and discontinuous aberrations due to obstruction by the secondary mirror and spider,realistically simulating the observation conditions of ground-based telescopes. By comparing with the Marechal criterion(0.075λ), we validate the effectiveness of the proposed approach. Experimental results show that the deep learning wavefront sensing approach can correct the distorted wavefront affect by high-order turbulence to close to the diffraction limit. We also analyze the limitations of this approach, using the direct zonal phase output method, where the residual wavefront stems from the fitting error. Furthermore, we have explored the wavefront reconstruction accuracy of different noise intensities and the central obstruction ratios. Within a noise intensity range of 1% –1.9%,the root mean square error(RMSE) of the residual wavefront is less than Marechal criterion. In the range of central obstruction ratios from 0.0 to 0.3 commonly used in ground-based telescopes, the RMSE of the residual wavefront is greater than 0.039λ and less than 0.041λ. This research provides an efficient and valid wavefront sensing approach for high-resolution observation with ground-based telescopes.
资助项目	National Natural Science Foundation of China (NSFC) [U2031140]
项目资助者	National Natural Science Foundation of China (NSFC) [U2031140]
语种	英语
学科领域	天文学 ; 天文学其他学科 ; 计算机科学技术 ; 人工智能
ISSN	1672-7975
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引用统计
文献类型	期刊论文
版本	出版稿
条目标识符	http://ir.ynao.ac.cn/handle/114a53/27913
专题	天文技术实验室
作者单位	1.Yunnan Observatories,Chinese Academy of Sciences; 2.University of Chinese Academy of Sciences
第一作者单位	中国科学院云南天文台
推荐引用方式 GB/T 7714	Liu DM,Liu H,Jin ZY. High accuracy deep learning wavefront sensing under high-order turbulence[J]. 天文技术与仪器(英文)/Astronomical Techniques and Instruments,2024,1(06):316-324.
APA	刘冬明,刘辉,&金振宇.(2024).High accuracy deep learning wavefront sensing under high-order turbulence.天文技术与仪器(英文)/Astronomical Techniques and Instruments,1(06),316-324.
MLA	刘冬明,et al."High accuracy deep learning wavefront sensing under high-order turbulence".天文技术与仪器(英文)/Astronomical Techniques and Instruments 1.06(2024):316-324.

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