A Bayesian method for fitting spectral energy distributions of galaxies with radiative transfer models

In this thesis I present the publicly available open-source spectral energy distribution (SED) fitting code SMART (Spectral energy distributions Markov chain Analysis with Radiative Transfer models). Implementing a Bayesian Markov chain Monte Carlo (MCMC) method, SMART fits the ultraviolet to millimetre SEDs exclusively with radiative transfer models that currently constitute four types of pre-computed libraries, which describe the starburst, active galactic nucleus (AGN) torus, host galaxy and polar dust components. These libraries are part of the collection of radiative transfer models named CYprus models for Galaxies and their NUclear Spectra (CYGNUS),
but also include other publicly available libraries of AGN torus models. An important novelty of SMART is that, although it fits exclusively with radiative transfer models, it takes comparable time to popular energy balance methods to run. Here we describe the key features of SMART and test it by fitting the multi-wavelength SEDs of the 42 local ultraluminous infrared galaxies (ULIRGs) that constitute the HERschel Ultraluminous Infrared Galaxy Survey (HERUS) sample. The Spitzer spectroscopy data of the HERUS ULIRGs are included in the fitting at a spectral resolution, which is matched to that of the radiative transfer models. We also present other results that
highlight the performance and versatility of SMART. We compare the main features of SMART with those of other popular SED fitting codes. SMART promises to be a useful tool for studying galaxy evolution in the James Webb Space Telescope (JWST) era.