Computer Science – Performance
Scientific paper
Dec 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005aas...20711202k&link_type=abstract
American Astronomical Society Meeting 207, #112.02; Bulletin of the American Astronomical Society, Vol. 37, p.1343
Computer Science
Performance
Scientific paper
We present an overview of a new BCG/red-sequence galaxy cluster catalog drawn from the Data Release 4 sample of Sloan Digital Sky Survey imaging. Galaxy clusters are selected by calculating the likelihood that each observed galaxy is a brightest cluster galaxy based on its color and magnitude, along with the degree to which galaxies cluster around it in color, magnitude, and space. This method provides a list of cluster locations together with estimates of their total galaxy content and accurate photometric redshifts (σ z < 0.02). The catalog covers the range 0.1 < z < 0.3 and includes 50,000 objects containing ten or more galaxies brighter than 0.4 L*. It successfully recovers luminous X-ray clusters, optically-selected clusters, and massive halos in mock galaxy catalogs with a low false-positive rate. Further details of the cluster finding algorithm and its performance, together with a description of the properties of the derived catalog will be presented.
Annis James
Becker Melanie
Bleem Lindsey
Evrard August E.
Johnston David
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