MaxBCG: A Red Sequence Galaxy Cluster Finder

Measurements of galaxy cluster abundances, clustering properties, and massto-light ratios in current and future surveys can provide important cosmological constraints. Digital wide-field imaging surveys, the recently-demonstrated fidelity of red-sequence cluster detection techniques, and a new generation of realistic mock galaxy surveys provide the means for construction of large, cosmologically-interesting cluster samples, whose selection and properties can be understood in unprecedented depth. We present the details of the “maxBCG” algorithm, a cluster-detection technique tailored to multi-band CCD-imaging data. MaxBCG primarily relies on an observational cornerstone of massive galaxy clusters: they are marked by an overdensity of bright, uniformly red galaxies. This detection scheme also exploits classical brightest cluster galaxies (BCGs), which are often found at the center of these same massive clusters. We study the algorithm herein through its performance on large, realistic, mock galaxy catalogs, Department of Physics, University of Michigan, Ann Arbor, MI 48104 NASA/Fermilab Astrophysics Center, Fermi National Accelerator Laboratory, Batavia, IL Kavli Institute for Cosmological Physics, The University of Chicago, Chicago, IL 60637 Department of Astronomy and Astrophysics and Enrico Fermi Institute, The University of Chicago, Chicago, IL 60637 Hubble Fellow Department of Physics, The University of Chicago, Chicago, IL 60637 Center for Cosmology and Particle Physics and Department of Physics, New York University, New York, NY 10003 Jet Propulsion Laboratory, Caltech, Pasadena, CA 91109