Bayesian Approaches to Infer the Physical Properties of Star-Forming Galaxies at Cosmic Dawn
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In this thesis, I seek to advance our understanding of galaxy formation and evolution in the early universe. Using the largest single project ever conducted by the Hubble Space Telescope (the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey, CANDELS) I use deep and wide broadband photometric imaging to infer the physical properties of galaxies from z=8.5 to z=1.5. First, I will present a study that extends the relationship between the star-formation rates (SFRs) and stellar masses (M*) of galaxies to 3.5<z<6.5, improves the constraints on the distant star-formation histories, and resolves an outstanding puzzle in the redshift evolution of the specific SFR (sSFR = SFR/M*). To improve determinations of distant galaxy SFRs, I then place new constrains on how dust is attenuated in galaxies. I calculate the Bayesian evidence for galaxies under different assumptions of their underlying dust-attenuation law. By modeling galaxy ultraviolet-to-near-IR broadband CANDELS data I produce Bayesian evidence towards the dust law in individual galaxies that is confirmed by their observed IR luminosities. Moreover, I find a tight correlation between the strength of attenuation in galaxies and their dust law, a relation reinforced by the results from radiative transfer simulations. Finally, I use the Bayesian methods developed in this thesis to study the number density of SFR in galaxies from z=8 to z=4, and resolve the current disconnect between its evolution and that of the stellar mass function. In doing so, I place the first constraints on the dust law of z>4 galaxies, finding it obeys a similar relation as found at z~2. I find a clear excess in number density at high SFRs. This new SFR function is in better agreement with the observed stellar mass functions, the few to-date infrared detections at high redshifts, and the connection to the observed distribution of lower redshift infrared sources. Together, these studies greatly improve our understanding of the galaxy star-formation histories, the nature of their dust attenuation, and the distribution of SFR among some of the most distant galaxies in the universe.
Salmon, Brett Weston Killebrew (2016). Bayesian Approaches to Infer the Physical Properties of Star-Forming Galaxies at Cosmic Dawn. Doctoral dissertation, Texas A & M University. Available electronically from