Modeling Galaxies in the Era of Precision Cosmology: An open source approach with Halotools
131 Campbell Hall
Andrew Hearin (Yale)
In this talk, I will review how models of the galaxy-halo connection can provide constraints on cosmology and insight into galaxy formation physics. Theoretical predictions in conventional formulations of these models are plagued by persistent systematic errors, for example due to uncertainty associated with "assembly bias". As galaxy surveys continue to provide ever more precise information on large-scale structure measurements, these theory-level systematics will place a ceiling on the reliability of the conclusions that can be drawn from traditional galaxy-halo techniques. In this talk, I'll describe how the open source Halotools package provides an object-oriented python framework designed to help remedy assembly bias and other systematics associated with nonlinearities in structure formation. Halotools is analogous to Boltzmann codes such as CMBFAST, CAMB and CLASS, but instead provides an optimized pipeline for populating mock galaxy catalogs into both low- and high-resolution simulations. I will conclude by describing how Halotools can be used to provide robust constraints on galaxy formation and help prepare the field of cosmology for the arrival of Stage IV dark energy experiments.