Precision cosmology with evolving x-ray clusters

Galaxy clusters are filled with an X-ray luminous plasma, the intracluster medium (ICM), which can be used to accurately measure many properties of the system. This dissertation collects three independent papers which constrain cosmological parameters through theoretical and numerical modeling of ICM observations. The projects are also unified by explicitly modeling ICM evolution and the effects of cluster dynamics on our results.; 1. The recently determined logN-logS statistic measures the surface density of clusters as a function of their X-ray flux. We combine an analytical model of the cluster mass function with constraints from the X-ray luminosity function at low redshifts, producing logN-logS predictions for a wide range of cosmological and evolutionary models. Evolution is modeled as a redshift dependence in the luminosity-mass relation, L_X ∝ Mp(1 + z) s. We find that likely cosmological models lie along the relationship s ∼ 6 Ω₀, with little dependence on other parameters.; 2. We perform a systematic analysis of ICM structure in a flux-limited sample of 45 nearby clusters. By constraining each cluster's density profile with its azimuthally averaged X-ray surface brightness, we measure ICM masses and density profiles, determine the local M _ICM-temperature relationship, and find a mildly significant variation of the ICM mass fraction with temperature. We employ an ensemble of simulated clusters to evaluate the effects of asphericity and adiabatic fluctuations on these results, obtaining a useful cosmological constraint of Ω ₀ ≤ 0.36 ± 0.01 h₅₀−1/2 .; 3. We create the first spectral temperature maps of simulated clusters, imaging each cluster at several steps in its evolutionary history and investigating the effect of mergers on the ICM. The best-fit spectral temperature T_s is typically found to be lower than the virial (mass-weighted) temperature by 10–20%, and we quantify their relationship in two different bandpasses. We show that more extreme errors are invariably associated with merging clusters, and construct an observational method for culling these from an ensemble.