Friends-of-friends groups and clusters in the 2SLAQ catalogue
Friends-of-friends groups and clusters in the 2SLAQ catalogue
S. Farrens 2
F. B. Abdalla 2
E. S. Cypriano 1
C. Sabiu 2
C. Blake 0
0 Centre for Astrophysics & Supercomputing, Swinburne University of Technology , PO Box 218, Hawthorn, VIC 3122 , Australia
1 Departamento de Astronomia , IAG-USP, Rua do Mata o 1226, 05508-090 Sa o Paulo , Brazil
2 Department of Physics & Astronomy, University College London , Gower Street, London WC1E 6BT
A B S T R A C T We present a catalogue of galaxy groups and clusters selected using a friends-of-friends (FoF) algorithm with a dynamic linking length from the 2dF-SDSS LRG and QSO (2SLAQ) luminous red galaxy survey. The linking parameters for the code are chosen through an analysis of simulated 2SLAQ haloes. The resulting catalogue includes 313 clusters containing 1152 galaxies. The galaxy groups and clusters have an average velocity dispersion of v = 467.97 km s1 and an average size of Rclt = 0.78 Mpc h1. Galaxies from regions of 1 deg2 and centred on the galaxy clusters were downloaded from the Sloan Digital Sky Survey Data Release 6. Investigating the photometric redshifts and cluster red sequence of these galaxies shows that the galaxy clusters detected with the FoF algorithm are reliable out to z 0.6. We estimate masses for the clusters using their velocity dispersions. These mass estimates are shown to be consistent with 2SLAQ mock halo masses. Further analysis of the simulation haloes shows that clipping out low-richness groups with large radii improves the purity of catalogue from 52 to 88 per cent, while retaining a completeness of 94 per cent. Finally, we test the two-point correlation function of our cluster catalogue. We find a best-fitting power-law model, (r) = (r/r0) , with parameters r0 = 24 4 Mpc h1 and = 2.1 0.2, which are in agreement with other low-redshift cluster samples and consistent with a cold dark matter universe.
galaxies; clusters; general - galaxies; distances and redshifts
1 I N T R O D U C T I O N
Galaxy clusters are the largest bound objects in the Universe and
are important structures for examining the distribution of matter and
how this evolves with time. Investigating how the mass function of
galaxy clusters changes with time provides an effective method for
constraining cosmological parameters (Press & Schechter 1974;
Peebles 1993; Haiman, Mohr & Holder 2001; Weller, Battye &
Kneissl 2002; Weller & Battye 2003).
The first galaxy cluster was unknowingly detected by Charles
Messier, who recorded the positions of 11 nebulae in the Virgo
cluster in the 18th century. Later evidence for the existence of
clusters of galaxies was provided in the work of Harlow Shapley
and Adelaide Ames in the 1930s (Shapley & Ames 1932). They
severely undermined the idea that galaxies are randomly distributed
throughout the Universe. Probably the most significant figure in
the pioneering of galaxy cluster detection was George Abell (Abell
1958). Abell surveyed around three quarters of the sky using
photographic plates, which meant that he had to identify the locations of
galaxy overdensities by eye. To avoid including field galaxies, Abell
defined galaxy clusters as regions 1.5 Mpc h1 in radius (the Abell
radius) containing 50 or more galaxies that are no more than two
magnitudes fainter than the third brightest member of the group.
Remarkably, later studies have confirmed a large number of Abell
clusters as being genuine bound structures. Due to the simplicity of
this 2D approach, however, serious problems can arise from, e.g.
inhomogeneities, photometric errors and projection effects. Bahcall
& Soneira (1983) found an excess of power in the angular
correlation function using Abell clusters, and van Haarlem, Frenk & White
(1997) show, using N-body simulations, that 1/3 of Abell clusters
have incorrect richness estimates and 1/3 of Abell richness class
R 1 clusters are missed. Around 30 years after Abells work,
hybrid photodigital surveys were able to improve upon the
photographic plate method for detecting clusters of galaxies (Maddox
et al. 1990). It was, however, the advent of digital CCD surveys that
brought about significant advances, a good example being surveys
such as the Sloan Digital Sky Survey (SDSS; York et al. 2000),
2dF Galaxy Redshift Survey (2dFGRS; Colless 1999), 6dF (Jones
et al. 2006) and the ongoing Galaxy and Mass Assembly (GAMA;
Driver et al. 2008). Large sky surveys like SDSS signify a major step
forward in obtaining galaxy data, however analysing that data can
be approached and interpreted in many different ways. Automated
algorithms supply a means of reducing subjectivity in the analysis
of large data sets. Finally, the availability of increasingly detailed
simulations in recent years has enabled more powerful tests of the
completeness and reliability of cluster catalogues.
In the last few decades many different algorithms have been
developed to find galaxy clusters. The Counts in Cells method (Couch
et al. 1991; Lidman & P (...truncated)