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29 March 2024
 
  » arxiv » astro-ph/0011557

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SDSS-RASS: Next Generation of Cluster-Finding Algorithms
R. Nichol ; C. Miller ; A. Connolly ; S. Chong ; C. Genovese ; A. Moore ; D. Reichart ; J. Schneider ; L. Wasserman ; J. Annis ; J. Brinkman ; H. Bohringer ; F. Castander ; R. Kim ; T. McKay ; M. Postman ; E. Sheldon ; I. Szapudi ; K. Romer ; W. Voges ;
Date 30 Nov 2000
Subject astro-ph
AbstractWe outline here the next generation of cluster-finding algorithms. We show how advances in Computer Science and Statistics have helped develop robust, fast algorithms for finding clusters of galaxies in large multi-dimensional astronomical databases like the Sloan Digital Sky Survey (SDSS). Specifically, this paper presents four new advances: (1) A new semi-parametric algorithm - nicknamed ``C4’’ - for jointly finding clusters of galaxies in the SDSS and ROSAT All-Sky Survey databases; (2) The introduction of the False Discovery Rate into Astronomy; (3) The role of kernel shape in optimizing cluster detection; (4) A new determination of the X-ray Cluster Luminosity Function which has bearing on the existence of a ``deficit’’ of high redshift, high luminosity clusters. This research is part of our ``Computational AstroStatistics’’ collaboration (see Nichol et al. 2000) and the algorithms and techniques discussed herein will form part of the ``Virtual Observatory’’ analysis toolkit.
Source arXiv, astro-ph/0011557
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