We identify galaxy groups and clusters in volume-limited samples of the Sloan Digital Sky Survey (SDSS) redshift survey, using a redshift-space friends-of-friends algorithm. We optimize the friends-of-friends linking lengths to recover galaxy systems that occupy the same dark matter halos, using a set of mock catalogs created by populating halos of N-body simulations with galaxies. Extensive tests with these mock catalogs show that no combination of perpendicular and line-of-sight linking lengths is able to yield groups and clusters that simultaneously recover the true halo multiplicity function, projected size distribution, and velocity dispersion. We adopt a linking length combination that yields, for galaxy groups with 10 or more members: a group multiplicity function that is unbiased with respect to the true halo multiplicity function; an unbiased median relation between the multiplicities of groups and their associated halos; a spurious group fraction of less than ∼1%; a halo completeness of more than ∼97%; the correct projected size distribution as a function of multiplicity; and a velocity dispersion distribution that is ∼20% too low at all multiplicities. These results hold over a range of mock catalogs that use different input recipes of populating halos with galaxies. We apply our group-finding algorithm to the SDSS data and obtain three group and cluster catalogs for three volume-limited samples that cover 3495.1 deg2 on the sky, go out to redshifts of 0.1, 0.068, and 0.045, and contain 57,138, 37,820, and 18,895 galaxies, respectively. We correct for incompleteness caused by fiber collisions and survey edges and obtain measurements of the group multiplicity function, with errors calculated from realistic mock catalogs. These multiplicity function measurements provide a key constraint on the relation between galaxy populations and dark matter halos.
All Science Journal Classification (ASJC) codes
- Astronomy and Astrophysics
- Space and Planetary Science