基于机器学习的自适应光学:综述

IF 15.3 1区物理与天体物理 Q1 OPTICS

Opto-Electronic Advances Pub Date : 2022-01-01 DOI:10.29026/oea.2022.200082

Youming Guo, Libo Zhong, Lei Min, Jiaying Wang, Yu Wu, Kele Chen, K. Wei, C. Rao

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引用次数: 41

摘要

自适应光学技术在过去的半个世纪里得到了发展，并且在大型地面望远镜中常规使用了30多年。虽然这项技术已经在各种应用中使用，但在过去的40年里，基本的设置和方法并没有改变。近年来，随着人工智能的快速发展，自适应光学将得到极大的发展。本文综述了基于机器学习的自适应光学几乎所有方面的最新进展。综述了智能自适应光学的研究现状。讨论了智能自适应光学的潜在优点和不足。

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Adaptive optics based on machine learning: a review

Adaptive optics techniques have been developed over the past half century and routinely used in large ground-based telescopes for more than 30 years. Although this technique has already been used in various applications, the basic setup and methods have not changed over the past 40 years. In recent years, with the rapid development of artificial intelligence, adaptive optics will be boosted dramatically. In this paper, the recent advances on almost all aspects of adaptive optics based on machine learning are summarized. The state-of-the-art performance of intelligent adaptive optics are reviewed. The potential advantages and deficiencies of intelligent adaptive optics are also discussed.

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来源期刊

Opto-Electronic Advances OPTICS-

CiteScore

19.30

自引率

7.10%

发文量

128

期刊介绍： Opto-Electronic Advances (OEA) is a distinguished scientific journal that has made significant strides since its inception in March 2018. Here's a collated summary of its key features and accomplishments: Impact Factor and Ranking: OEA boasts an impressive Impact Factor of 14.1, which positions it within the Q1 quartiles of the Optics category. This high ranking indicates that the journal is among the top 25% of its field in terms of citation impact. Open Access and Peer Review: As an open access journal, OEA ensures that research findings are freely available to the global scientific community, promoting wider dissemination and collaboration. It upholds rigorous academic standards through a peer review process, ensuring the quality and integrity of the published research. Database Indexing: OEA's content is indexed in several prestigious databases, including the Science Citation Index (SCI), Engineering Index (EI), Scopus, Chemical Abstracts (CA), and the Index to Chinese Periodical Articles (ICI). This broad indexing facilitates easy access to the journal's articles by researchers worldwide.