Galaxy models

Galaxy models at the interface of theory and observations

In Sun et al. (2019), we aimed to develop a physically-motivated framework for extracting astrophysical information about the multi-phase ISM of galaxies from multi-tracer LIM data sets. Such a framework bridges the gap between (1) simple empirical scaling relations often used for LIM forecasts and (2) sophisticated numerical recipes for simulating the production of emission lines. We fit a semi-empirical prescription of the infrared spectral energy distribution to the observed angular anisotropy of the cosmic infrared background and leveraged the observed dust-to-gas ratio to derive physical properties of galaxy hosting halos, including the dust mass, gas mass, metallicity, etc. These quantities are then used to compute the luminosity of various target lines for LIM surveys, such as HI, CO, [NII], and [CII] lines, each tracing a different phase of the ISM. Synergies among these LIM measurements therefore provide valuable information for coarse-grain averaged properties of the ISM and their cosmic evolution.

In Furlanetto et al. (2017), we develop a simple analytic model to describe z > 6 galaxies, an exciting population of galaxies being extensively studied by recent/ongoing/future deep near-infrared surveys by HST and JWST. The model builds on top of the assumption that galaxies grow through smooth accretion onto dark matter halos, which we describe by matching halo number density across redshift. It allows physically motivated extrapolation to earlier times and fainter luminosities, limited by choices of feedback parameters that can reasonably fit the galaxy data available. Such a “minimalist” framework helps us develop intuition for the range of expectations permitted by simple models of high-redshift galaxies that build on our understanding of “normal” galaxy evolution.