使用多层随机并行梯度下降算法对三反射镜消像散望远镜进行对准
Alignment of three mirror anastigmat telescopes using a multilayered stochastic parallel gradient descent algorithm
AI总结：
针对三反射镜消像散望远镜初始装配后的早期相位对准问题，提出多层SPGD算法，以视场聚焦光斑尺寸为反馈、波前峰谷误差为监测指标，将望远镜粗对准至可移交精细自适应光学系统的水平。
摘要：
当望远镜在初次装配后未能在探测器上获得合理的点扩散函数或可探测的波前质量时，在天空上进行粗略的相位对准至关重要。在利用闭环自适应光学系统之前，天文台需要一种策略来主动充分对准望远镜，以便进行精细波前传感。本文提出了一种使用随机并行梯度下降（SPGD）算法的早期对准方法，该算法对三反射镜消像散望远镜设计中的光学元件执行随机扰动。SPGD算法将驱动望远镜，直到波前误差低于精细自适应光学系统可接受的范围，从而完成望远镜的移交。采用视场内的聚焦光斑尺寸作为SPGD算法的馈送参数，并监测波前峰谷误差值，以直接比较我们的机械能力与衍射受限成像和精细波前传感的对准目标。
英文摘要：
When a telescope doesn't reach a reasonable point spread function on the detector or detectable wavefront quality after initial assembly, a coarse phase alignment on-sky is crucial. Before utilizing a closed loop adaptive optics system, the observatory needs a strategy to actively align the telescope sufficiently for fine wavefront sensing. This paper presents a method of early-stage alignment using a stochastic parallel-gradient-descent (SPGD) algorithm which performs random perturbations to the optics of a three mirror anastigmat telescope design. The SPGD algorithm will drive the telescope until the wavefront error is below the acceptable range of the fine adaptive optics system to hand the telescope over. The focused spot size over the field of view is adopted as a feed parameter to the SPGD algorithm and wavefront peak-to-valley error values are monitored to directly compare our mechanical capabilities to our alignment goal of diffraction limited imaging and fine wavefront sensing.
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。
