Riggs, Stephen David (2022) Galaxy distributions within and around observed and simulated groups. Doctoral thesis (PhD), University of Sussex.

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Abstract

This thesis explores the properties and distributions of galaxies within and around galaxy groups, making use of galaxy clustering statistics. We include both observations and simulations in this analysis.

In the first part we explore the properties of galaxies in the GAMA survey and the L-GALAXIES and SHARK semi-analytic models. We examine which elements of the models affect the predictions for galaxy stellar masses, luminosities and clustering, and find that satellite galaxy physics plays an important role in the small-scale clustering.

In the second part we determine the cross-correlation between groups and galaxies in the GAMA survey, to explore both the group profile and the large-scale bias around groups, and provide comparisons against the IllustrisTNG simulations and L-GALAXIES model. Using marked clustering statistics we find that the clustering depends strongly on the group masses, but has very little dependence on galaxy masses.

We then explore the differences in distributions of galaxies in groups in full-physics and dark matter-only simulations. Using satellites matched between the IllustrisTNG simulations and their dark matter-only equivalents, we find that the satellites reside closer to the group centre and have enhanced survival times in the full-physics simulations. We split the satellites of IllustrisTNG into those which possess dark matter-only equivalents and those which do not, and create empirical models for both of these populations.

Finally, we apply these empirical corrections in the L-GALAXIES and SHARK models, and explore the impact this has on their predictions for galaxy clustering.

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:	24 Aug 2022 09:32
Last Modified:	24 Aug 2022 09:32
URI:	http://sro.sussex.ac.uk/id/eprint/107539

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