基于Landweber和Landweber-Kaczmarz迭代的金字塔传感器非线性波前重构方法
Non-linear wavefront reconstruction methods for pyramid sensors using Landweber and Landweber-Kaczmarz iteration
摘要：
用于金字塔波前传感器的精确和鲁棒的波前重建方法是高需求的，因为这些传感器计划成为目前正在开发的用于地基望远镜的许多仪器的一部分。金字塔传感器以非线性方式将入射波前与其测量值相关联。然而，几乎所有现有的重建算法都是基于模型的线性化。当测量的相位信息很小时，线性金字塔传感器响应的假设在闭环AO中是合理的，但是由于取决于系统的不可防止的误差（诸如非公共路径像差），在现实中可能是不合理的。为了解决金字塔传感器数据波前重构的非线性逆问题，本文提出了两种基于非线性Landweber迭代和Landweber-Kaczmarz迭代的新方法。使用这些算法，我们经历了高质量的波前估计，特别是对非调制传感器仍然保持数值工作可行的大规模AO系统。
英文摘要：
Accurate and robust wavefront reconstruction methods for pyramid wavefront sensors are in high demand as these sensors are planned to be part of many instruments currently under development for ground based telescopes. The pyramid sensor relates the incoming wavefront and its measurements in a non-linear way. Nevertheless, almost all existing reconstruction algorithms are based on a linearization of the model. The assumption of a linear pyramid sensor response is justifiable in closed loop AO when the measured phase information is small but may not be reasonable in reality due to unpreventable errors depending on the system such as non common path aberrations. In order to solve the non-linear inverse problem of wavefront reconstruction from pyramid sensor data we introduce two new methods based on the non-linear Landweber and Landweber-Kaczmarz iteration. Using these algorithms we experience high-quality wavefront estimation especially for the non-modulated sensor by still keeping the numerical effort feasible for large-scale AO systems.
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。
