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Mana, Annalisa (2013): Optically selected galaxy clusters as a cosmological probe. Dissertation, LMU München: Fakultät für Physik
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Abstract

Multi-wavelength large-scale surveys are currently exploring the Universe and establishing the cosmological scenario with extraordinary accuracy. There has been recently a significant theoretical and observational progress in efforts to use clusters of galaxies as probes of cosmology and to test the physics of structure formation. Galaxy clusters are the most massive gravitationally bound systems in the Universe, which trace the evolution of the large-scale structure. Their number density and distribution are highly sensitive to the underlying cosmological model. The constraints on cosmological parameters which result from observations of galaxy clusters are complementary with those from other probes. This dissertation examines the crucial role of clusters of galaxies in confirming the standard model of cosmology, with a Universe dominated by dark matter and dark energy. In particular, we examine the clustering of optically selected galaxy clusters as a useful addition to the common set of cosmological observables, because it extends galaxy clustering analysis to the high-peak, high-bias regime. The clustering of galaxy clusters complements the traditional cluster number counts and observable-mass relation analyses, significantly improving their constraining power by breaking existing calibration degeneracies. We begin by introducing the fundamental principles at the base of the concordance cosmological model and the main observational evidence that support it. We then describe the main properties of galaxy clusters and their contribution as cosmological probes. We then present the theoretical framework of galaxy clusters number counts and power spectrum. We revise the formulation and calibration of the halo mass function, whose high mass tail is populated by galaxy clusters. In addition to this, we give a prescription for modelling the cluster redshift space power spectrum, including an effective modelling of the weakly non-linear contribution and allowing for an arbitrary photometric redshift smoothing. Some definitions concerning the study of non-Gaussian initial conditions are presented, because clusters can provide constraints on these models. We dedicate a Chapter to the data we use in our analysis, namely the Sloan Digital Sky Survey maxBCG optical catalogue. We describe the data sets we derived from this large sample of clusters and the corresponding error estimates. Specifically, we employ the cluster abundances in richness bins, the weak-lensing mass estimates and the redshift-space power spectrum, with their respective covariance matrices. We also relate the cluster masses to the observable quantity (richness) by means of an empirical scaling relation and quantify its scatter. In the next Chapter we present the results of our Monte Carlo Markov Chain analysis and the cosmological constraints obtained. With the maxBCG sample, we simultaneously constrain cosmological parameters and cross-calibrate the mass-observable relation. We find that the inclusion of the power spectrum typically brings a 50% improvement in the errors on the fluctuation amplitude and the matter density. Constraints on other parameters are also improved, even if less significantly. In addition to the cluster data, we also use the CMB power spectra from WMAP7, which further tighten the confidence regions. We also apply this method to constrain models of the early universe through the amount of primordial non-Gaussianity of the initial density perturbations (local type) obtaining consistent results with the latest constraints. In the last Chapter, we introduce some preliminary calculations on the cross-correlation between clusters and galaxies, which can provide additional constraining power on cosmological models. In conclusion, we summarise our main achievements and suggest possible future developments of research.

Abstract