On the Cluster Physics of Sunyaev-Zel'dovich and X-ray Surveys III: Measurement Biases and Cosmological Evolution of Gas and Stellar Mass Fractions

Abstract

Gas masses tightly correlate with the virial masses of galaxy clusters, allowing for a precise determination of cosmological parameters by means of large-scale X-ray surveys. However, according to recent Suzaku X-ray measurements, gas mass fractions, f_gas, appear to be considerably larger than the cosmic mean at the virial radius, R_200, questioning the accuracy of the cosmological parameter estimations. Here, we use a large suite of cosmological hydrodynamical simulations to study measurement biases of f_gas. We employ different variants of simulated physics, including radiative gas physics, star formation, and thermal feedback by active galactic nuclei. Computing the mass profiles in 48 angular cones, whose footprints partition the sphere, we find anisotropic gas and total mass distributions that imply an angular variance of f_gas at the level of 30%. This anisotropic distribution originates from the recent formation epoch of clusters and from the strong internal baryon-to-dark-matter density bias. In the most extreme cones, f_gas can be biased high by a factor of two at R_200 in massive clusters, thereby providing a potential explanation for high f_gas measurements by Suzaku. While projection lowers this factor, there are other measurement biases that may (partially) compensate. We find that at R_200, f_gas is biased high by 20% when assuming hydrostatic equilibrium masses, i.e., neglecting the kinetic pressure, and by another ~10-20% due to the presence of density clumping. At larger radii, both measurement biases increase dramatically. While the cluster sample variance of the true f_gas decreases to a level of 5% at R_200, the sample variance that includes both measurement biases remains fairly constant at the level of 10-20%. The constant redshift evolution of f_gas within R_500 for massive clusters is encouraging for using gas masses to derive cosmological parameters.