The large-scale structure of the Universe is delineated by the spatial distributions of galaxies and clusters of galaxies. This thesis describes three projects concerned with the use of galaxies and clusters as cosmological probes, following the presentation of necessary background material in Chapter 1.
Chapter 2 is concerned with spatial correlations of clusters of galaxies. After comprehensively reviewing previous work addressing this topic from both observational and theoretical points of view, we present, test and apply an important new method for computing theoretical cluster correlations. Our method combines the theory of peaks in Gaussian random fields with the evolution of the cosmological density field by the Zeldoviclr Approximation: this is the first analytic calculation of the cluster correlation function to take account of the nonlinear evolution of the cosmological density field on cluster scales. We find good agreement between our results and those from recent numerical simulations, except for the richest cluster samples, for which our method yields stronger clustering. Comparison of our predicted correlations with those observed in recent optical cluster samples reveal that the once-popular Einstein - de Sitter Cold Dark Matter (CDM) model lacks the large-scale power required to match the observed clustering. We also apply our method in the first theoretical study of the spatial correlations of ROSAT clusters. Our results here favour cosmogonies with more large-scale power than CDM, in accordance with those we obtained from optical cluster samples.
The projects in Chapters 3 and 4 are concerned with galaxy clustering. In Chapter 3 we consider the redshift-space clustering of samples of IRAS galaxies selected on the basis of their dust emission temperature, having argued that there might be a relation
between the temperature of the galaxy and density of the environment in which the galaxy is located. We find, however, no conclusive evidence for a difference in the clustering strength of the “warm” and “cool” samples in redshift space. This validates the use of redshift samples of IRAS galaxies as tracers of large-scale structure, as well as constraining models of merger-induced star formation.
In Chapter 4 we show, through the novel analysis of liigli-resolution numerical simulation data, how the observed power spectra of optical and IRAS galaxy clustering constrain the initial power spectrum of density fluctuations and the relation between the galaxy distribution and the underlying density field. Motivated by recent N-body/hydrodynamic simulations, we employ a biasing prescription in which the local galaxy number density at redshift zero is determined by the present local mass density. We determine which combinations of initial power spectrum and biasing prescription are consistent with the observed clustering of optical galaxies and use the observed relation between the distributions of optical and IRAS galaxies to predict corresponding redshift-spa.ee IRASpower spectra. These are compared with observations, as are the pairwise velocity dispersions predicted by the models. In this way, building, in part, on our results from Chapter 3, we are able to construct a coherent picture of galaxy clustering which is in accord with our results 011 cluster correlations from Chapter 2, showing that galaxies and clusters are consistent probes of the large-scale structure of the Universe.