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Measurement of Galaxy Cluster Sizes, Radial Profiles, and Luminosity Functions from SDSS Photometric Data

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arxiv astro-ph/0410467 v3 pith:Y35SPHKP submitted 2004-10-20 astro-ph

Measurement of Galaxy Cluster Sizes, Radial Profiles, and Luminosity Functions from SDSS Photometric Data

classification astro-ph
keywords clusterclustersgalaxyrichnessfunctiongalaxiesfindingluminosity
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Imaging data from the Sloan Digital Sky Survey is used to measure the empirical size-richness relation for a large sample of galaxy clusters. Using population subtraction methods, we determine the radius at which the cluster galaxy number density is 200/Omega_m times the mean galaxy density, without assuming a model for the radial distribution of galaxies in clusters. If these galaxies are unbiased on Mpc scales, this galaxy-density-based R_200 reflects the characteristic radii of clusters. We measure the scaling of this characteristic radius with richness over an order of magnitude in cluster richness, from rich clusters to poor groups. We use this information to examine the radial profiles of galaxies in clusters as a function of cluster richness, finding that the concentration of the galaxy distribution decreases with richness and is systematically lower than the concentrations measured for dark matter profiles in N-body simulations. Using these scaled radii, we investigate the behavior of the cluster luminosity function, and find that it is well matched by a Schechter function for galaxies brighter than M_r = -18 only after the central galaxy has been removed. We find that the luminosity function varies with richness and with distance from the cluster center, underscoring the importance of using an aperture that scales with cluster mass to compare physically equivalent regions of these different systems. We note that the lowest richness systems in our catalog have properties consistent with those expected of the earliest-forming halos; our cluster-finding algorithm, in addition to reliably finding clusters, may be efficient at finding fossil groups.

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