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29 March 2024 |
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Article overview
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Optical Cluster-Finding with An Adaptive Matched-Filter Technique: Algorithm and Comparison with Simulation | Feng Dong
; Elena Pierpaoli
; James E. Gunn
; Risa H. Wechsler
; | Date: |
6 Sep 2007 | Abstract: | We present a modified adaptive matched filter algorithm designed to identify
clusters of galaxies in wide-field imaging surveys such as the Sloan Digital
Sky Survey. The cluster-finding technique is fully adaptive to imaging surveys
with spectroscopic coverage, multicolor photometric redshifts, no redshift
information at all, and any combination of these within one survey. It works
with high efficiency in multi-band imaging surveys where photometric redshifts
can be estimated with well-understood error distributions. Tests of the
algorithm on realistic mock SDSS catalogs suggest that the detected sample is
~85% complete and over 90% pure for clusters with masses above 1.0*10^{14}
h^{-1} M_solar and redshifts up to z=0.45. The errors of estimated cluster
redshifts from maximum likelihood method are shown to be small (typically less
that 0.01) over the whole redshift range with photometric redshift errors
typical of those found in the Sloan survey. Inside the spherical radius
corresponding to a galaxy overdensity of Delta=200, we find the derived cluster
richness Lambda_{200} a roughly linear indicator of its virial mass M_{200},
which well recovers the relation between total luminosity and cluster mass of
the input simulation. | Source: | arXiv, 0709.0759 | Services: | Forum | Review | PDF | Favorites |
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