Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.585477
Title: Determining the star formation histories of resolved stellar populations
Author: Small, Emma
Awarding Body: Liverpool John Moores University
Current Institution: Liverpool John Moores University
Date of Award: 2012
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Abstract:
The question of how galaxies form and evolve throughout the age of the Universe is at the forefront of astrophysics research. In the past two decades, an observational technique has emerged that uses resolved stellar populations of nearby galaxies to trace their evolutionary history. This is based on the fact that stars are a fossil record of the star formation history (SFH), which is defined as the star formation rate and chemical evolution as a function of time. Star formation histories allow the study of galaxy evolution on a case by case basis. This is complementary to large scale surveys of distant galaxies that give a general picture of galaxy evolution through time. Colour magnitude diagrams are the most useful tool in studies of resolved stellar pop- ulations because they contain information in both age and metallicity. However, ex- tracting this information is difficult owing to various degeneracies between these two parameters in the CMD. Currently synthetic CMD methods are used to perform this type of analysis, where the SFH is determined by matching the number density of stars across the binned observed CMD with synthetic populations. This thesis presents FIReS (Fitting Isochrones to Resolved Stars), a code that has been developed to determine SFHs of resolved stellar populations using a new maximum likelihood method. The SFH is represented as a linear combination of simple stellar populations, which are modelled by isochrones. FIReS fits multiple isochrones to the data using a likelihood function based on individual stellar probabilities. A genetic algorithm is used to optimize the isochrone weights in order to determine the SFH that most likely produced the observed CMD. The likelihood can also be used to determine the mean distance and reddening of the population. iii
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.585477  DOI: Not available
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