Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.645122
Title: Modelling galaxies in the high redshift universe
Author: Crawford, D. M.
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2006
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Abstract:
I present predictions for the high redshift universe, where dust is known to play an important role in influencing the observed magnitudes, colours and properties of galaxies. I demand that an acceptable model must first yield reasonably accurate predictions for the local universe before being tested at high redshift. Not only will this ground the models in reality, it will then help assess whether a ‘standard’ semi-analytic model can reproduce facets of the high redshift universe without recourse to new physics. I construct mock surveys in an attempt to account for three distinct classes of object: Lyman Break Galaxies (LBGs), a population of dusty star forming galaxies at redshift 3, Extremely Red Objects (EROs), galaxies with (R-K) > 5 uncovered in deep K-band surveys, and Submillimetre Galaxies (SMGs) detected in blank field SCUBA surveys. Global trends and individual galaxy properties are explored and compared with reality. Overlaps between distinct populations are investigated, and the fate of extreme high redshift objects is followed through time, shedding light on relationships between evolutionary phases of galaxies. It has been suggested that SMGs and EROs are the progenitors of local giant ellipticals, and I can assess the validity of this theory within the framework of the simulated survey volumes. SMGs are among the most massive objects present at that particular point in cosmic history. Such extreme objects will be highly biased towards over densities in the dark matter field, and thus should exhibit strong clustering. The SCUBA Half-Degree Extragalactic Survey (SHADES) aims to detect a statistically significant number of SMGs with an unambiguous measure of their clustering properties in mind. I present equivalent predictions for the model SMGs, a technique that has great potential in assisting the planning and interpretation of future deep surveys aimed at probing the earliest stages of galaxy formation and the origins of the most massive galaxies we see today.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.645122  DOI: Not available
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