2012/11/20 by Marc Gentile, F. Courbin, Gentile, Marc +3
Engineering · Mathematics · Physics and Astronomy · #Adaptive optics and wavefront sensing #Advanced Measurement and Metrology Techniques #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Physical sciences #Statistical and numerical algorithms
paper · pdf · doi:10.48550/arxiv.1211.4847
openalex publication_date 2012/11/20 · openalex created_date 2022/09/04 · openalex updated_date 2026/07/28
It is anticipated that the large sky areas covered by planned wide-field weak\nlensing surveys will reduce statistical errors to such an extent that\nsystematic errors will instead become the dominant source of uncertainty. It is\ntherefore crucial to devise numerical methods to measure galaxy shapes with the\nleast possible systematic errors. We present a simple "forward deconvolution"\nmethod, gfit, to measure galaxy shapes given telescope and atmospheric\nsmearings, in the presence of noise. The method consists in fitting a single 2D\nelliptical S 'ersic profile to the data, convolved with the point spread\nfunction. We applied gfit to the data proposed in the GRavitational lEnsing\nAccuracy Testing 2010 (GREAT10) Galaxy Challenge. In spite of its simplicity,\ngfit obtained the lowest additive bias\n(\√(\A)=0.057\×10-4) on the shear power spectrum among\ntwelve different methods and the second lowest multiplicative bias\n(\M/2=0.583\×10-2). It remains that gfit is a fitting\nmethod and is therefore affected by noise bias. However, the simplicity of the\nunderlying galaxy model combined with the use of an efficient customized\nminimization algorithm allow very competitive performances, at least on the\nGREAT10 data, for a relatively low computing time.\n