Use this URL to cite or link to this record in EThOS:
Title: Models of hierarchical galaxy formation
Author: Helly, John Christopher
ISNI:       0000 0001 3552 3870
Awarding Body: Durham University
Current Institution: Durham University
Date of Award: 2003
Availability of Full Text:
Access from EThOS:
Access from Institution:
A semi-analytic galaxy formation model, N-body GALFORM, is developed which uses outputs from an N-body simulation to follow the merger histories of dark matter halos and treats baryonic processes using the semi-analytic model of Cole et al. We find that, apart from limited mass resolution, the only significant differences between this model and the Monte-Carlo based model of Cole et al. are due to known inaccuracies in the distribution of halo progenitor masses in the Monte-Carlo method. N-body GALFORM is used to compare Smooth Particle Hydrodynamics (SPH) and semi-analytic calculations of radiative cooling in the absence of star formation. We consider two cases: firstly, a simulation of a representative volume of the Universe with relatively poor mass resolution, and, secondly, a high resolution simulation of the formation of a single galaxy. We find good agreement between the models in terms of the mass of gas which cools in each halo, the masses of individual galaxies, and the spatial distribution of the galaxies. The semi-analytic model is then compared with a realistic, high-resolution galaxy simulation which includes prescriptions for star formation and feedback. A semi-analytic model without feedback is found to best reproduce the masses of the simulated galaxy and its progenitors. This model is used to populate a large volume with semi-analytic galaxies. The resulting luminosity function has an order of magnitude too many galaxies at high and low luminosities. We conclude that, while SPH and semi-analytic cooling calculations are largely consistent and therefore likely to be reasonably reliable, current numerical models of galaxy formation still contain major uncertainties due to the treatment of feedback, which will lead them to predict very different galaxy populations. Further work is required to find simulation algorithms which can simultaneously produce realistic individual galaxies and a population with reasonable statistical properties.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available