Constraints on galaxy formation models from the galaxy stellar mass function and its evolution

Abstract

We explore the parameter space of the semi-analytic galaxy formation model GALFORM, studying the constraints imposed by measurements of the galaxy stellar mass function (GSMF) and its evolution. We use the Bayesian Emulator method to quickly eliminate vast implausible volumes of the parameter space and zoom in on the most interesting regions, allowing us to identify a set of models that match the observational data within model uncertainties. We find that the GSMF strongly constrains parameters related to quiescent star formation in discs, stellar and AGN feedback and threshold for disc instabilities, but weakly restricts other parameters. Constraining the model using local data alone does not usually select models that match the evolution of the GSMF well. Nevertheless, we show that a small subset of models provides acceptable match to GSMF data out to redshift 1.5. We explore the physical significance of the parameters of these models, in particular exploring whether the model provides a better description if the mass loading of the galactic winds generated by starbursts ($\beta_{0,\text{burst}}$) and quiescent disks ($\beta_{0,\text{disc}}$) is different. Performing a principal component analysis of the plausible volume of the parameter space, we write a set of relations between parameters obeyed by plausible models with respect to GSMF evolution. We find that while $\beta_{0,\text{disc}}$ is strongly constrained by GSMF evolution data, constraints on $\beta_{0,\text{burst}}$ are weak. Although it is possible to find plausible models for which $\beta_{0,\text{burst}} = \beta_{0,\text{disc}}$, most plausible models have $\beta_{0,\text{burst}}>\beta_{0,\text{disc}}$, implying - for these - larger SN feedback efficiency at higher redshifts.