Cosmological Constraints from Cluster X-ray Morphologies

Mathematics – Logic

Scientific paper

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Scientific paper

We use a representative sample of galaxy clusters to constrain the range of cluster X-ray morphologies. After developing and testing quantitative, objective, and reproducible measures of cluster X-ray morphology, we apply these measures to a sample of 65\ Einstein IPC cluster observations to constrain the intrinsic distributions of (i) emission weighted centroid variation w_{vec x}, (ii) emission weighted axial ratio eta , (iii) emission weighted orientation theta_o , and (iv) measures of the radial fall--off, alpha and beta . For each cluster we use a Monte--Carlo procedure to determine the effects of Poisson noise, detector imperfections, and foreground/background X-ray point sources. We then use the range of cluster X-ray morphology to constrain three generic cosmological models (Omega =1, Omega_o =0.2, and Omega_o =0.2 & lambda_o =0.8). We evolve eight sets of Gaussian random initial conditions consistent with an effective power spectrum P(k)~ k(-1) on cluster scales. Using a sample of 24 numerical cluster simulations (3times8 ) which include gravity and gas physics (but no cooling or ejection from galaxies), we compare observed cluster X-ray morphologies with the X-ray morphologies of clusters simulated with different underlying cosmological models. Specifically, we build artificial ensembles with the same distributions in the number of cluster photons, X-ray temperature, and cluster redshift as the\ Einstein ensemble; we then compare the observed and simulated distributions in w_{vec x}, eta , and alpha . The comparisons indicate that (i) these three morphological characteristics are sensitive to the underlying cosmological model, and (ii) galaxy clusters with the observed range of X-ray morphology are very unlikely in low Omega_o cosmologies. The analysis favors the Omega =1 model, though some discrepancies remain. We discuss the effects of changing the initial conditions and of including additional physics in the simulations.

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