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基于区域分解的预处理累积重建器:一种用于金字塔波前传感器的快速波前重建方法。

Preprocessed cumulative reconstructor with domain decomposition: a fast wavefront reconstruction method for pyramid wavefront sensor.

作者信息

Shatokhina Iuliia, Obereder Andreas, Rosensteiner Matthias, Ramlau Ronny

机构信息

Industrial Mathematics Institute, Johannes Kepler University Linz, Linz, Austria.

出版信息

Appl Opt. 2013 Apr 20;52(12):2640-52. doi: 10.1364/AO.52.002640.

Abstract

We present a fast method for the wavefront reconstruction from pyramid wavefront sensor (P-WFS) measurements. The method is based on an analytical relation between pyramid and Shack-Hartmann sensor (SH-WFS) data. The algorithm consists of two steps--a transformation of the P-WFS data to SH data, followed by the application of cumulative reconstructor with domain decomposition, a wavefront reconstructor from SH-WFS measurements. The closed loop simulations confirm that our method provides the same quality as the standard matrix vector multiplication method. A complexity analysis as well as speed tests confirm that the method is very fast. Thus, the method can be used on extremely large telescopes, e.g., for eXtreme adaptive optics systems.

摘要

我们提出了一种从金字塔波前传感器(P-WFS)测量结果进行波前重建的快速方法。该方法基于金字塔传感器和夏克-哈特曼传感器(SH-WFS)数据之间的解析关系。该算法包括两个步骤:首先将P-WFS数据转换为SH数据,然后应用带域分解的累积重建器,即一种从SH-WFS测量结果进行波前重建的重建器。闭环模拟证实,我们的方法提供的质量与标准矩阵向量乘法方法相同。复杂度分析以及速度测试证实该方法非常快速。因此,该方法可用于极大的望远镜,例如用于极端自适应光学系统。

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