The C4 Clustering Algorithm: Clusters of Galaxies in the Sloan Digital   Sky Survey
  We present the "C4 Cluster Catalog", a new sample of 748 clusters of galaxies identified in the spectroscopic sample of the Second Data Release (DR2) of the Sloan Digital Sky Survey (SDSS). The C4 cluster--finding algorithm identifies clusters as overdensities in a seven-dimensional position and color space, thus minimizing projection effects which plagued previous optical clusters selection. The present C4 catalog covers ~2600 square degrees of sky with groups containing 10 members to massive clusters having over 200 cluster members with redshifts. We provide cluster properties like sky location, mean redshift, galaxy membership, summed r--band optical luminosity (L_r), velocity dispersion, and measures of substructure. We use new mock galaxy catalogs to investigate the sensitivity to the various algorithm parameters, as well as to quantify purity and completeness. These mock catalogs indicate that the C4 catalog is ~90% complete and 95% pure above M_200 = 1x10^14 solar masses and within 0.03 <=z <= 0.12. The C4 algorithm finds 98% of X-ray identified clusters and 90% of Abell clusters within 0.03 <= z <= 0.12. We show that the L_r of a cluster is a more robust estimator of the halo mass (M_200) than the line-of-sight velocity dispersion or the richness of the cluster. L_r. The final SDSS data will provide ~2500 C4 clusters and will represent one of the largest and most homogeneous samples of local clusters. 
Christopher J. Miller (CTIO/NOAO), Robert Nichol, Dan Reichart, Risa   Wechsler, August Evrard, James Annis, Timothy McKay, ...