Abstract
Galaxies are generally treated as point particles in clustering analysis. However, these objects have physical and stellar population properties that must be taken into account if one wants to study the environmental effects on galaxy evolution. In this work, we applied a statistical method to investigate the role of environment in driving galaxy properties based on the marked correlation function. This methodology was applied to a galaxy sample drawn from the Sloan Digital Sky Survey Data Release 7, where the clustering of galaxies was weighted by particular galaxy properties, like luminosity and stellar mass, thus more directly quantifying the correlations between these attributes and large-scale environment. We show that marked statistics are powerful to reproduce environmental trends for variables like luminosities and stellar masses, as well as to quantify the relative importance of them with respect to the environment. For low density regions in the local universe, mark correlations relative to the mean are stronger compared to dense regions. This implies that the clustering of stellar mass, for instance, is more sensitive to environments associated to individual halos in close galaxy pairs than to massive halos found in clusters, where the correlations don't show any difference relative to the mean. We conclude that in nearby galaxy clusters, dominated by massive objects, galaxies are equally clustered (marked correlation = average clustering). On the other hand, galaxies in low density regions span a wide range in stellar mass (halo sizes) where the correlations appear more dramatically.
