中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 云南天文台
  3. 中国科学院云南天文台
  4. 天文技术实验室
High accuracy deep learning wavefront sensing under high-order turbulence

文献类型：期刊论文

作者Liu DM(刘冬明)1,2; Liu H(刘辉)1; Jin ZY(金振宇)1
刊名天文技术与仪器(英文)/Astronomical Techniques and Instruments
出版日期2024-11
卷号1期号:06页码:316-324
ISSN号1672-7975
DOI10.61977/ati2024052
产权排序第1完成单位
英文摘要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. 
学科主题天文学 ; 天文学其他学科 ; 计算机科学技术 ; 人工智能
分类号P111 ; P111.44
URL标识查看原文
资助项目National Natural Science Foundation of China (NSFC) [U2031140]
语种英语
资助机构National Natural Science Foundation of China (NSFC) [U2031140]
版本出版稿
源URL[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
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.

入库方式： OAI收割

来源：云南天文台

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。