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arXiv 1807.04341astro-ph.IMastro-ph.EP
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高帧频地面高对比度成像系统准静态像差的实时估计与校正

Real-time estimation and correction of quasi-static aberrations in ground-based high contrast imaging systems with high frame-rates

Alexander T. Rodack, Jared R. Males, Olivier Guyon, Benjamin A. Mazin, Michael P. Fitzgerald, Dimitri Mawet

摘要:

地面高对比度成像探测系外行星的成功部分取决于区分准静态散斑和行星强度信号的能力,准静态散斑是由自适应光学(AO)系统未校正的像差(称为非共路像差(NCPA))引起的。Frazin(ApJ,2013)引入了一种后处理算法,证明科学相机和波阵面传感器(WFS)中的同时毫秒曝光可以与统计推断程序一起使用,以确定系列扩展NCPA系数和行星信号。我们证明,通过仿真,使用该算法在闭环AO系统中,实时估计和校正的准静态NCPA是可能的,而无需单独的变形镜(DM)探头。因此,使用这种技术可以消除可能被误认为行星信号的准静态散斑,而不需要新的光学硬件,提高了地基系外行星探测的效率。在我们的模拟中,我们探讨了Frazin算法(FA)的行为及其收敛性对Strehl比,NCPA强度和算法搜索基函数数量等因素的准确估计的依赖性。然后,我们应用这些知识来模拟在接近理想的设置中实时运行该算法。然后,我们讨论的适应,可以作出的算法,以提高其实时性能,并在模拟中显示其功效。最后的模拟测试的技术的弹性对不完善的知识的AO剩余相位,激励使用这种技术在一个真正的闭环极端AO系统,如SCExAO或MagAO-X的可行性分析,在计算复杂性和准确性的估计准静态NCPA校正。

英文摘要:

The success of ground-based, high contrast imaging for the detection of exoplanets in part depends on the ability to differentiate between quasi-static speckles caused by aberrations not corrected by adaptive optics (AO) systems, known as non-common path aberrations (NCPAs), and the planet intensity signal. Frazin (ApJ, 2013) introduced a post-processing algorithm demonstrating that simultaneous millisecond exposures in the science camera and wavefront sensor (WFS) can be used with a statistical inference procedure to determine both the series expanded NCPA coefficients and the planetary signal. We demonstrate, via simulation, that using this algorithm in a closed-loop AO system, real-time estimation and correction of the quasi-static NCPA is possible without separate deformable mirror (DM) probes. Thus the use of this technique allows for the removal of the quasi-static speckles that can be mistaken for planetary signals without the need for new optical hardware, improving the efficiency of ground-based exoplanet detection. In our simulations, we explore the behavior of the Frazin Algorithm (FA) and the dependence of its convergence to an accurate estimate on factors such as Strehl ratio, NCPA strength, and number of algorithm search basis functions. We then apply this knowledge to simulate running the algorithm in real-time in a nearly ideal setting. We then discuss adaptations that can be made to the algorithm to improve its real-time performance, and show their efficacy in simulation. A final simulation tests the technique's resilience against imperfect knowledge of the AO residual phase, motivating an analysis of the feasibility of using this technique in a real closed-loop Extreme AO system such as SCExAO or MagAO-X, in terms of computational complexity and the accuracy of the estimated quasi-static NCPA correction.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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