English

Probing Cosmology with Dark Matter Halo Sparsity Using X-ray Cluster Mass Measurements

Cosmology and Nongalactic Astrophysics 2018-08-08 v2

Abstract

We present a new cosmological probe for galaxy clusters, the halo sparsity. This characterises halos in terms of the ratio of halo masses measured at two different radii and carries cosmological information encoded in the halo mass profile. Building upon the work of Balmes et al. (2014) we test the properties of the sparsity using halo catalogs from a numerical N-body simulation of (2.62.6 Gpc/h)3^3 volume with 409634096^3 particles. We show that at a given redshift the average sparsity can be predicted from prior knowledge of the halo mass function. This provides a quantitative framework to infer cosmological parameter constraints using measurements of the sparsity of galaxy clusters. We show this point by performing a likelihood analysis of synthetic datasets with no systematics, from which we recover the input fiducial cosmology. We also perform a preliminary analysis of potential systematic errors and provide an estimate of the impact of baryonic effects on sparsity measurements. We evaluate the sparsity for a sample of 104 clusters with hydrostatic masses from X-ray observations and derive constraints on the cosmic matter density Ωm\Omega_m and the normalisation amplitude of density fluctuations at the 88 Mpc h1^{-1} scale, σ8\sigma_8. Assuming no systematics, we find Ωm=0.42±0.17\Omega_m=0.42\pm 0.17 and σ8=0.80±0.31\sigma_8=0.80\pm 0.31 at 1σ1\sigma, corresponding to S8σ8Ωm=0.48±0.11S_8\equiv \sigma_8\sqrt{\Omega_m}=0.48\pm 0.11. Future cluster surveys may provide opportunities for precise measurements of the sparsity. A sample of a few hundreds clusters with mass estimate errors at a few percent level can provide competitive cosmological parameter constraints complementary to those inferred from other cosmic probes.

Keywords

Cite

@article{arxiv.1711.00480,
  title  = {Probing Cosmology with Dark Matter Halo Sparsity Using X-ray Cluster Mass Measurements},
  author = {P. S. Corasaniti and S. Ettori and Y. Rasera and M. Sereno and S. Amodeo and M. -A. Breton and V. Ghirardini and D. Eckert},
  journal= {arXiv preprint arXiv:1711.00480},
  year   = {2018}
}

Comments

20 pages, 15 figures; working example extended to other overdensities, detailed analysis of systematic error from hydrostatic mass bias, overall results unchanged. ApJ accepted version. Halo sparsity code available at https://github.com/pierste75/Halo_Sparsity