On-sky validation of image-based adaptive optics wavefront sensor referencing
On-sky validation of image-based adaptive optics wavefront sensor referencing
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基于图像的自适应光学波前传感器参考的空中验证
DOI：
10.1051/0004-6361/202141514
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Vievard S?bastien
中科院分区：
文献类型：
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作者：
Skaf Nour;Guyon Olivier;Gendron ?ric;Ahn Kyohoon;Bertrou-Cantou Arielle;Boccaletti Anthony;Cranney Jesse;Currie Thayne;Deo Vincent;Edwards Billy;Ferreira Florian;Gratadour Damien;Lozi Julien;Norris Barnaby;Sevin Arnaud;Vidal Fabrice;Vievard S?bastien
区分真实的系外行星信号和残余斑点噪声是高对比度成像（HCI）的一个关键挑战。散斑是由大气湍流和仪器光学引入的快速、慢速和静态波前像差的组合产生的。虽然在过去十年中开发的波前控制技术在最大限度地减少快速大气残差方面表现出了希望，但慢速和静态像差（如非共路像差（NCPA））仍然是系外行星探测的关键限制因素。自适应光学（AO）环路的波前传感器（WFS）看不到NCPA，因此难以校正它们。AimsWe建议提高AO校正图像中缓慢和静态散斑的识别和抑制。被称为直接增强波前启发式优化（DrWHO）的算法对静态和准静态像差（包括NCPA）执行频繁的补偿操作，以提高图像对比度。它适用于通用AO系统以及HCI systems.MethodsBy改变WFS参考在每一个迭代的算法（几十秒），DrWHO改变AO系统的收敛点，导致它对静态和缓慢的像差的补偿机制。参考计算使用迭代幸运成像方法，每次迭代更新WFS参考，最终有利于高质量的焦平面images.ResultsWe验证了这一概念，通过数值模拟和对SCExAO仪器在8.2米斯巴鲁望远镜的天空测试。模拟结果表明，82%的NCPA的校正快速收敛。在可见光（750 nm）下运行10分钟以上进行空中测试。我们引入了一个通量浓度（FC）度量量化的点扩散函数（PSF）的质量和测量相比，pre-DrWHO imag.ConclusionsThe DrWHO算法是一个强大的焦平面波前传感校准方法，已成功地证明了对天空的15.7%的改善。它不依赖于模型，也不需要波前传感器校准或线性。它与不同的波前控制方法兼容，并且可以进一步优化速度和效率。该算法可以用于科学观测，从而在观测过程中实现更好的PSF质量和稳定性。
ContextDifferentiating between a true exoplanet signal and residual speckle noise is a key challenge in high-contrast imaging (HCI). Speckles result from a combination of fast, slow, and static wavefront aberrations introduced by atmospheric turbulence and instrument optics. While wavefront control techniques developed over the last decade have shown promise in minimizing fast atmospheric residuals, slow and static aberrations such as non-common path aberrations (NCPAs) remain a key limiting factor for exoplanet detection. NCPAs are not seen by the wavefront sensor (WFS) of the adaptive optics (AO) loop, hence the difficulty in correcting them.AimsWe propose to improve the identification and rejection of slow and static speckles in AO-corrected images. The algorithm known as the Direct Reinforcement Wavefront Heuristic Optimisation (DrWHO) performs a frequent compensation operation on static and quasi-static aberrations (including NCPAs) to boost image contrast. It is applicable to general-purpose AO systems as well as HCI systems.MethodsBy changing the WFS reference at every iteration of the algorithm (a few tens of seconds), DrWHO changes the AO system point of convergence to lead it towards a compensation mechanism for the static and slow aberrations. References are calculated using an iterative lucky-imaging approach, where each iteration updates the WFS reference, ultimately favoring high-quality focal plane images.ResultsWe validated this concept through both numerical simulations and on-sky testing on the SCExAO instrument at the 8.2-m Subaru telescope. Simulations show a rapid convergence towards the correction of 82% of the NCPAs. On-sky tests were performed over a 10 min run in the visible (750 nm). We introduced a flux concentration (FC) metric to quantify the point spread function (PSF) quality and measure a 15.7% improvement compared to the pre-DrWHO image.ConclusionsThe DrWHO algorithm is a robust focal-plane wavefront sensing calibration method that has been successfully demonstrated on-sky. It does not rely on a model and does not require wavefront sensor calibration or linearity. It is compatible with different wavefront control methods, and can be further optimized for speed and efficiency. The algorithm is ready to be incorporated in scientific observations, enabling better PSF quality and stability during observations.
DOI：
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发表时间：
2008
期刊：
影响因子：
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作者：
J. Spyromilio
通讯作者：
J. Spyromilio
DOI：
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发表时间：
1992
期刊：
Problems in veterinary medicine
影响因子：
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作者：
S. Altman
通讯作者：
S. Altman