Galaxy Clusters in Hubble Volume Simulations: Cosmological Constraints from Sky Survey Populations
We use giga-particle N-body simulations to study galaxy cluster populations in Hubble Volumes of LCDM (Omega_m=0.3, Omega_Lambda=0.7) and tCDM (Omega_m=1) world models. Mapping past light-cones of locations in the computational space, we create mock sky surveys of dark matter structure to z~1.4 over 10,000 sq deg and to z~0.5 over two full spheres. Calibrating the Jenkins mass function at z=0 with samples of ~1.5 million clusters, we show that the fit describes the sky survey counts to <~20% acccuracy over all redshifts for systems larger than poor groups (M>5e13 Msun/h). Fitting the observed local temperature function determines the ratio beta of specific thermal energies in dark matter and intracluster gas. We derive a scaling with power spectrum normalization beta \propto sigma8^{5/3}, and measure a 4% error on sigma8 arising from cosmic variance in temperature-limited cluster samples. Considering distant clusters, the LCDM model matches EMSS and RDCS X-ray-selected survey observations under economical assumptions for intracluster gas evolution. Using transformations of mass-limited cluster samples that mimic sigma8 variation, we explore SZ search expectations for a 10 sq deg survey complete above 10^{14} Msun/h. Cluster counts are shown to be extremely sensitive to sigma8 uncertainty while redshift statistics, such as the sample median, are much more stable. For LCDM, the characteristic temperature at fixed sky surface density is a weak function of redshift, implying an abundance of hot clusters at z>1. Assuming constant beta, four kT>8 keV clusters lie at z>2 and 40 kT>5 keV clusters lie at z>3 on the whole sky. Detection of Coma-sized clusters at z>1 violate LCDM at 95% confidence if their surface density exceeds 0.003 per sq deg, or 120 on the whole sky.