Semi-analytic model of galaxy formation with radiative feedback during the Epoch of Reionisation

Srisawat, Chaichalit (2016) Semi-analytic model of galaxy formation with radiative feedback during the Epoch of Reionisation. Doctoral thesis (PhD), University of Sussex.

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Several hundred million years after the Big Bang, the Epoch of Reionisation(EoR) started as the photons from the first objects ionised neutral baryons in the Universe. The observations such as the Gunn-Peterson troughs in quasar absorption spectra and the linear polarisation of the cosmic microwave background (CMB) impose strong constraints on reionisation models of the EoR. Recent data provide the rest-frame ultraviolet luminosity of galaxies up to redshift 10. However, the observation of star formations in low mass galaxies is still not practicable. Their star formations are expected to be suppressed by the increase of ionised baryons and greatly affect the reionisation models.
We develop a flexible pipeline which utilises the Munich Semi-Analytic Model of galaxy formation, L-Galaxies, and a semi-numerical modelling of cosmic reionisation. This combination allows us to create a self-consistent reionisation simulation in computational models of galaxy formation. We use this pipeline on a high resolution cosmological Nbody simulation to produce the redshift evolution of the star forming galaxies during the EoR. Comparisons of the properties of mock galaxies and the growth of ionised hydrogen bubbles suggest that the reionisation history heavily depends on the suppression models used in the modeling of dwarf galaxy formation. During this research, some numerical flaws of merger tree generation algorithms were identified. We investigated the origins of these problems and present suggestions for solving them.

Item Type: Thesis (Doctoral)
Schools and Departments: School of Mathematical and Physical Sciences > Physics and Astronomy
Subjects: Q Science > QB Astronomy > QB0495 Descriptive astronomy > QB0856 Galaxies
Depositing User: Library Cataloguing
Date Deposited: 22 Nov 2016 11:23
Last Modified: 13 Dec 2018 14:24

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