Clustering of Galaxy Clusters in CDM Universes
Abstract
We use very large cosmological N--body simulations to obtain accurate predictions for the two-point correlations and power spectra of mass-limited samples of galaxy clusters. We consider two currently popular cold dark matter (CDM) cosmogonies, a critical density model (CDM) and a flat low density model with a cosmological constant (CDM). Our simulations each use particles to follow the mass distribution within cubes of side Gpc (CDM) and Gpc (CDM) with a force resolution better than of the cube side. We investigate how the predicted cluster correlations increase for samples of increasing mass and decreasing abundance. Very similar behaviour is found in the two cases. The correlation length increases from -- 13Mpc for samples with mean separation Mpc to -- 27Mpc for samples with Mpc. The lower value here corresponds to CDM and the upper to CDM. The power spectra of these cluster samples are accurately parallel to those of the mass over more than a decade in scale. Both correlation lengths and power spectrum biases can be predicted to better than 10% using the simple model of Sheth, Mo & Tormen (2000). This prediction requires only the linear mass power spectrum and has no adjustable parameters. We compare our predictions with published results for the APM cluster sample. The observed variation of correlation length with richness agrees well with the models, particularly for CDM. The observed power spectrum (for a cluster sample of mean separation Mpc) lies significantly above the predictions of both models.
Cite
@article{arxiv.astro-ph/0005259,
title = {Clustering of Galaxy Clusters in CDM Universes},
author = {J. M. Colberg and S. D. M. White and N. Yoshida and T. J. MacFarland and A. Jenkins and C. S. Frenk and F. R. Pearce and A. E. Evrard and H. M. P. Couchman and G. Efstathiou and J. A. Peacock and P. A. Thomas},
journal= {arXiv preprint arXiv:astro-ph/0005259},
year = {2009}
}
Comments
9 pages, 5 figures. Accepted for publication in MNRAS. Minor changes