Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.632754
Title: Untangling the physical components of galaxies using infrared spectra
Author: Hurley, Peter Donald
ISNI:       0000 0004 5363 1009
Awarding Body: University of Sussex
Current Institution: University of Sussex
Date of Award: 2014
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Abstract:
The two main physical processes that underpin galaxy evolution are star formation and accretion of mass in active galactic nuclei (AGN). Understanding how contributions from these processes vary across cosmic time requires untangling their relative contributions. The infrared part of the electromagnetic spectrum contains a number of AGN and star formation diagnostics e.g. emission lines from ionised gas or polyaromatic hydrocarbons (PAHs), and the shape of the continuum. Despite the higher resolution of data from Spitzer's IRS spectrograph, separating out emission from star formation and AGN is carried out using limited spectral features or simplistic templates. In the first part of this thesis, I show how sophisticated data analysis techniques can make full use of the wealth of spectral data. I demonstrate how the popular multivariate technique, Principal Component Analysis (PCA), can classify different types of ultra luminous infrared galaxies (ULIRGs), whilst providing a simple set of spectral components that provide better fits than state-of-the art radiative transfer models. I show how an alternative multivariate technique, Non-Negative Matrix Factorisation (NMF) is more appropriate by applying it to over 700 extragalactic spectra from the CASSIS database and demonstrating its capability in producing spectral components that are physically intuitive, allowing the processes of star formation and AGN activity to be clearly untangled. Finally, I show how rotational transition lines from carbon monoxide and water, observed by the Herschel Space Observatory, provides constraints on the physical conditions within galaxies. By coupling the radiative transfer code, RADEX, with the nested sampling routine, Multinest, I carry out Bayesian inference on the CO spectral line energy distribution ladder of the nearby starburst galaxy, IC342. I also show that water emission lines provide important constraints the conditions of the ISM of on one of the most distant starburst galaxies ever detected, HFLS3.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.632754  DOI: Not available
Keywords: QB0495 Descriptive astronomy ; QB0799 Stars
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