基于神经网络的金字塔传感器非线性波前重构

IF 3.3 3区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS Publications of the Astronomical Society of the Pacific Pub Date : 2023-11-01 DOI:10.1088/1538-3873/acfdcb
Alison P. Wong, Barnaby R. M. Norris, Vincent Deo, Peter G. Tuthill, Richard Scalzo, David Sweeney, Kyohoon Ahn, Julien Lozi, Sébastien Vievard, Olivier Guyon
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引用次数: 0

摘要

摘要金字塔波前传感器(PyWFS)因其高灵敏度在自适应光学系统中得到越来越广泛的应用。PyWFS的主要缺点是它本质上是非线性的,这意味着经典的线性波前重建技术在高波前误差时面临着性能的显著降低,特别是当金字塔未调制时。在本文中,我们考虑了神经网络(NNs)取代广泛使用的矩阵向量乘法(MVM)控制的潜在用途。我们的目标是测试一个假设,即神经网络建模非线性的能力将使其比MVM控制具有明显的优势。我们使用斯巴鲁日冕极端自适应光学系统(SCExAO)仪器上获取的日间数据,比较了MVM线性重构器与密集神经网络的性能。在第一组实验中,我们产生了由14种泽尼克模式产生的波前和不同调制半径(25、50、75和100 mas)下的PyWFS响应。我们发现,在所有调制下,神经网络允许更精确的波前重建,在PyWFS非线性变得显著的情况下,性能差异会增加。在第二组实验中,我们生成了一个类似大气的波前数据集,并证实了神经网络优于线性重构器。后者采用SCExAO实时计算机软件作为基准。这些结果表明,神经网络可以很好地改进线性重构器,并在不久的将来带来AO性能的飞跃。
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Nonlinear Wave Front Reconstruction from a Pyramid Sensor using Neural Networks
Abstract The pyramid wave front sensor (PyWFS) has become increasingly popular to use in adaptive optics (AO) systems due to its high sensitivity. The main drawback of the PyWFS is that it is inherently nonlinear, which means that classic linear wave front reconstruction techniques face a significant reduction in performance at high wave front errors, particularly when the pyramid is unmodulated. In this paper, we consider the potential use of neural networks (NNs) to replace the widely used matrix vector multiplication (MVM) control. We aim to test the hypothesis that the NN's ability to model nonlinearities will give it a distinct advantage over MVM control. We compare the performance of a MVM linear reconstructor against a dense NN, using daytime data acquired on the Subaru Coronagraphic Extreme Adaptive Optics system (SCExAO) instrument. In a first set of experiments, we produce wavefronts generated from 14 Zernike modes and the PyWFS responses at different modulation radii (25, 50, 75, and 100 mas). We find that the NN allows for a far more precise wave front reconstruction at all modulations, with differences in performance increasing in the regime where the PyWFS nonlinearity becomes significant. In a second set of experiments, we generate a data set of atmosphere-like wavefronts, and confirm that the NN outperforms the linear reconstructor. The SCExAO real-time computer software is used as baseline for the latter. These results suggest that NNs are well positioned to improve upon linear reconstructors and stand to bring about a leap forward in AO performance in the near future.
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来源期刊
Publications of the Astronomical Society of the Pacific
Publications of the Astronomical Society of the Pacific 地学天文-天文与天体物理
CiteScore
6.70
自引率
5.70%
发文量
103
审稿时长
4-8 weeks
期刊介绍: The Publications of the Astronomical Society of the Pacific (PASP), the technical journal of the Astronomical Society of the Pacific (ASP), has been published regularly since 1889, and is an integral part of the ASP''s mission to advance the science of astronomy and disseminate astronomical information. The journal provides an outlet for astronomical results of a scientific nature and serves to keep readers in touch with current astronomical research. It contains refereed research and instrumentation articles, invited and contributed reviews, tutorials, and dissertation summaries.
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