A Comprehensive Understanding of the Light from Galaxies
I am developing an empirical galaxy formation model that self-consistently models the galaxy growth histories within the context of cosmological structure formation. Currently, these models requires calibrating on observationally inferred galaxy physical properties. However, the limited information in a single observed galaxy spectral energy distribution (SED) and therefore the inherent uncertainties in modeling mean that we at least have a ~0.35 dex uncertainty on those physical properties. The next-generation empirical galaxy formation model will forward model and directly match all the observed SEDs across cosmic time. The self-consistent evolution of the galaxy properties should reduce the uncertainty on galaxy properties down to ~0.15 dex level. I will discuss recent progress and some scientific questions we can start to answer with this approach. I will also discuss how generative models could be used to make inferences at the pixel level (field-level inference) for galaxies possible. Key outcomes include a fully physical, self-consistent picture of galaxy stellar masses, star formation histories, dust, and metallicity from z = 0 to 15; significantly reduced uncertainties on the galaxy-halos connection; and highly realistic mock catalogs and images for arbitrary current and future surveys that self-consistently match the latest observations.