Probabilistic cross-identification of galaxies with realistic clustering

被引：3
|
作者：
Mallinar, N. [1 ,3 ]
Budavari, T. [2 ,3 ,4 ]
Lemson, G. [4 ]
机构：
[1] Johns Hopkins Univ, Dept Math, Baltimore, MD 21218 USA
[2] Johns Hopkins Univ, Dept Appl Math & Stat, Baltimore, MD 21218 USA
[3] Johns Hopkins Univ, Dept Comp Sci, Baltimore, MD 21218 USA
[4] Johns Hopkins Univ, Dept Phys & Astron, Baltimore, MD 21218 USA
来源：
ASTRONOMY AND COMPUTING | 2017年 / 20卷
基金：
美国国家科学基金会;
关键词：
Methods: statistical; Astrometry; Catalogs; Surveys; Galaxies: statistics; DIGITAL SKY SURVEY;
D O I：
10.1016/j.ascom.2017.06.001
中图分类号：
P1 [天文学];
学科分类号：
0704 ;
摘要：
Probabilistic cross-identification has been successfully applied to a number of problems in astronomy from matching simple point sources to associating stars with unknown proper motions and even radio observations with realistic morphology. Here we study the Bayes factor for clustered objects and focus in particular on galaxies to assess the effect of typical angular correlations. Numerical calculations provide the modified relationship, which (as expected) suppresses the evidence for the associations at the shortest separations where the 2-point auto-correlation function is large. Ultimately this means that the matching probability drops at somewhat shorter scales than in previous models. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码：83 / 86
页数：4
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