The Cluster Distribution as a Test for Dark Matter Models. I: Clustering Properties

Abstract

We present extended simulations of the distribution of galaxy clusters in different dark matter models, using an optimized version of the Zel'dovich approximation. Six different dark matter models are studied: Standard CDM, Open CDM, Tilted CDM, Cold + Hot DM, low-density CDM with cosmological constant, and low Hubble constant ($h=0.3$) CDM. We compare simulations with an Abell/ACO redshift sample. We find that the models that best reproduce the clustering of the real data sets are the Cold + Hot DM model and the CDM model with a cosmological constant. The probability density function of all models and data is always well approximated by a lognormal distribution. We also find that the linear biasing parameter for the simulated clusters is nearly constant over a large range of scales, but its value depends on the model. We also note that the abundances of clusters predicted by the Press-Schechter theory provide strong constraints on these models: only the Cold + Hot DM model and the low-H CDM model appear to produce the correct number-density of clusters. Taking this constraint together with the cluster clustering statistics leads one to conclude that the best of our models is the Cold + Hot DM scenario.