4.7 Article

3D-Matched-Filter galaxy cluster finder - I. Selection functions and CFHTLS Deep clusters

Journal

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 406, Issue 1, Pages 673-688

Publisher

WILEY-BLACKWELL
DOI: 10.1111/j.1365-2966.2010.16720.x

Keywords

methods: numerical; galaxies: abundances; galaxies: clusters: general; galaxies: luminosity function; mass function; cosmology: theory; large-scale structure of Universe

Funding

  1. European DUEL RTN [MRTN-CT-2006-036133]
  2. German Ministry for Science and Education (BMBF) through DESY [05AV5PDA/3]
  3. German Science Foundation (DFG) [TR33]

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We present an optimized galaxy cluster finder, 3D-Matched-Filter (3D-MF), which utilizes galaxy cluster radial profiles, luminosity functions and redshift information to detect galaxy clusters in optical surveys. This method is an improvement over other matched-filter methods, most notably through implementing redshift slicing of the data to significantly reduce line-of-sight projections and related false positives. We apply our method to the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) Deep fields, finding similar to 170 galaxy clusters deg-2 in the 0.2 < z < 1.0 redshift range. Future surveys such as LSST and JDEM can exploit 3D-MF's automated methodology to produce complete and reliable galaxy cluster catalogues. We determine the reliability and accuracy of the statistical approach of our method through a thorough analysis of mock data from the Millennium Simulation. We detect clusters with 100 per cent completeness for M(200) >= 3.0 x 1014 M(circle dot), 88 per cent completeness for M(200) >= 1.0 x 1014 M(circle dot) and 72 per cent completeness well into the 1013 M(circle dot) cluster mass range. We show a 36 per cent multiple detection rate for cluster masses >= 1.5 x 1013 M(circle dot) and a 16 per cent false detection rate for galaxy clusters > rsim5 x 1013 M(circle dot), reporting that for clusters with masses less than or similar to 5 x 1013 M(circle dot) false detections may increase up to similar to 24 per cent. Utilizing these selection functions we conclude that our galaxy cluster catalogue is the most complete CFHTLS Deep cluster catalogue to date.

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