A GMBCG Galaxy Cluster Catalog of 55,424 Rich Clusters from SDSS DR7

TL;DR

This paper introduces a new algorithm, GMBCG, for detecting galaxy clusters in SDSS data, resulting in the largest optical cluster catalog with high completeness and purity, especially for rich clusters.

Contribution

The paper presents a novel GMBCG algorithm that effectively identifies galaxy clusters using the red sequence and BCG features, producing the largest catalog from SDSS DR7.

Findings

Catalog contains over 55,000 rich clusters

High completeness and purity for clusters with 15+ members

Effective detection across redshift range 0.1 to 0.55

Abstract

We present a large catalog of optically selected galaxy clusters from the application of a new Gaussian Mixture Brightest Cluster Galaxy (GMBCG) algorithm to SDSS Data Release 7 data. The algorithm detects clusters by identifying the red sequence plus Brightest Cluster Galaxy (BCG) feature, which is unique for galaxy clusters and does not exist among field galaxies. Red sequence clustering in color space is detected using an Error Corrected Gaussian Mixture Model. We run GMBCG on 8240 square degrees of photometric data from SDSS DR7 to assemble the largest ever optical galaxy cluster catalog, consisting of over 55,000 rich clusters across the redshift range from 0.1 < z < 0.55. We present Monte Carlo tests of completeness and purity and perform cross-matching with X-ray clusters and with the maxBCG sample at low redshift. These tests indicate high completeness and purity across the full redshift range for clusters with 15 or more members.