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Tracing star formation and AGN activity at radio frequencies

My research has focused on locating and measuring star formation and AGN activity in different environments with interferometric and single-dish radio observations. As my first PhD project, I studied the complex interaction between an intermediate redshift (z 0.3) starburst galaxy and a nearby ( 7 kpc separation) QSO using sub-arcsecond VLA observations. I found new evidence for jet-induced star formation activity in the companion galaxy, making the system a strong candidate for this rare, and potentially important process in the early Universe. In my second paper, I investigated the infrared-radio correlation (IRRC) of spheroid- and disc-dominated galaxies in the COSMOS field out to z 1.5. With 1.4 GHz data and Herschel photometry I found that the redshift evolution reported in recent works is due to an increasing radio excess emission associated with spheroid-dominated galaxies, compared to disc-dominated ones, i.e. the ‘purest' star-forming systems in our sample. I theorize that the extra radio power in spheroid-dominated systems is due to low-level AGN activity, even though these sources were not identified by most commonly-used diagnostics as AGN hosts. This finding will significantly increase the accuracy of future high-redshift radio surveys measuring star formation. In my third project I assembled and analysed the largest-to-date low-z IRRC sample of galaxies. I demonstrated the importance of selection effects influencing IRRC statistics, and carried out an improved IRRC analysis that yielded more accurate measures of the correlation's properties. With rich ancillary data it will provide insight into the physical processes that give rise to the IRRC. Finally, I adopted an MCMC-based model optimization to fit a radiative transfer model to ammonia line spectra of a binary molecular cloud core. I determined the physical structures and the masses of the cores and found they are gravitationally unbound.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:759578
Date January 2018
CreatorsMolnár, Dániel Csaba
PublisherUniversity of Sussex
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://sro.sussex.ac.uk/id/eprint/79453/

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