Benson, Andrew John (2000) Galaxy formation and clustering in a hierarchical universe. Doctoral thesis, Durham University.
In this Thesis we describe a semi-analytic model of galaxy formation. We apply the model to the problem of galaxy clustering and show that the dependence of galaxy formation efficiency on halo mass leads to a scale-dependent bias in the distribution of galaxies relative to the distribution of mass. Remarkably, this results in a correlation function in a flat, Ωo = 0.3, CDM model that is close to a power-law over four orders of magnitude in amplitude and which agrees well with the correlation function of galaxies measured in the APM survey. The galaxy velocity dispersion is ~ 40% lower than that of the dark matter. Biases cause the redshift space correlation functions of model galaxies and dark matter to be remarkably similar to each other. A dependence of clustering strength on galaxy luminosity exists for extremely bright galaxies and for galaxies selected either by morphology or by colour. We present predictions for the reionization of the intergalactic medium by stars in high-redshift galaxies, including the effects of absorption by interstellar gas and dust. We combine our model with an N-body simulation to calculate the temperature anisotropies induced in the cosmic microwave background by reionization. Finally, we test key aspects of the model. We use ROSAT PSPC data to search for extended X-ray emission from the halos of three nearby, massive, late-type galaxies. The luminosity lies well below the model prediction. We discuss this discrepancy and consider a number of possible explanations. By comparing the statistical properties of galaxies in our model with those of galaxies formed in cosmological hydrodynamics simulations we show that the two techniques produce broadly consistent predictions. However, individual statistics, such as the galaxy mass function, may differ by factors of 2-4. We identify possible reasons for these discrepancies, thereby highlighting avenues for future work to explore.
|Item Type:||Thesis (Doctoral)|
|Award:||Doctor of Philosophy|
|Copyright:||Copyright of this thesis is held by the author|
|Deposited On:||01 Aug 2012 11:44|