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题名: The point spread function reconstruction by using Moffatlets - I
作者: Li, Bai-Shun; Li, Guo-Liang; Cheng, Jun; Peterson, John; Cui, Wei
刊名: RESEARCH IN ASTRONOMY AND ASTROPHYSICS
出版日期: 2016
卷号: 16, 期号:9, 页码:139
英文摘要: Shear measurement is a crucial task in current and future weak lensing survey projects. The reconstruction of the point spread function (PSF) is one of the essential steps involved in this process. In this work, we present three different methods, Gaussianlets, Moffatlets and Expectation Maximization Principal Component Analysis (EMPCA), and quantify their efficiency on PSF reconstruction using four sets of simulated Large Synoptic Survey Telescope (LSST) star images. Gaussianlets and Moffatlets are two different sets of basis functions whose profiles are based on Gaussian and Moffat functions respectively. EMPCA is a statistical method performing an iterative procedure to find the principal components (PCs) of an ensemble of star images. Our tests show that: (1) Moffatlets always perform better than Gaussianlets. (2) EMPCA is more compact and flexible, but the noise existing in the PCs will contaminate the size and ellipticity of PSF. By contrast, Moffatlets keep the size and ellipticity very well.
内容类型: 期刊论文
URI标识: http://libir.pmo.ac.cn/handle/332002/16887
Appears in Collections:星系宇宙学和暗能量研究团组_期刊论文

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