The galaxy luminosity function around groups

We present a study on the variations of the luminosity function of galaxies around clusters in a numerical simulation with semi-analytic galaxies, attempting to detect these variations in the 2dF Galaxy Redshift Survey. We subdivide the simulation box into equal-density regions around clusters, which we assume can be achieved by selecting objects at a given normalized distance ( r/r(rms), where r(rms) is an estimate of the halo radius) from the group centre. The semi-analytic model predicts important variations in the luminosity function out to r/r(rms) similar or equal to 5. In brief, variations in the mass function of haloes around clusters ( large dark matter haloes with M > 1012 h(-1) M-circle dot) lead to cluster central regions that present a high abundance of bright galaxies ( high M* values) as well as low-luminosity galaxies ( high a); at r/r(rms) similar or equal to 3 there is a lack of bright galaxies, which shows the depletion of galaxies in the regions surrounding clusters ( minimum in M* and a), and a tendency to constant luminosity function parameters at larger cluster-centric distances. We take into account the observational biases present in the real data by reproducing the peculiar velocity effect on the redshifts of galaxies in the simulation box, and also by producing mock catalogues. We find that excluding from the analysis galaxies which in projection are close to the centres of the groups provides results that are qualitatively consistent with the full simulation box results. When we apply this method to mock catalogues of the 2dF Galaxy Redshift Survey ( 2dFGRS) and the 2PIGG catalogue of groups, we find that the variations in the luminosity function are almost completely erased by the Finger of God effect; only a lack of bright galaxies at r/r(rms) similar or equal to 3 can be marginally detected in the mock catalogues. The results from the real 2dFGRS data show a clearer detection of a dip in M* and a for r/r(rms) = 3, consistent with the semi-analytic predictions.