An empirical model to form and evolve galaxies in dark matter halos

Shijie Li, Youcai Zhang, Xiaohu Yang, Huiyuan Wang, Dylan Tweed, Chengze Liu, Lei Yang, Feng Shi, Yi Lu, Wentao Luo, Jianwen Wei

Published 2016-05-17Version 1

Based on the star formation histories (SFH) of galaxies in halos of different masses, we develop an empirical model to grow galaxies in dark mattet halos. This model has very few ingredients, any of which can be associated to observational data and thus be efficiently assessed. By applying this model to a very high resolution cosmological $N$-body simulation, we predict a number of galaxy properties that are a very good match to relevant observational data. Namely, for both centrals and satellites, the galaxy stellar mass function (SMF) up to redshift $z\simeq4$ and the conditional stellar mass functions (CSMF) in the local universe are in good agreement with observations. In addition, the 2-point correlation is well predicted in the different stellar mass ranges explored by our model. Furthermore, after applying stellar population synthesis models to our stellar composition as a function of redshift, we find that the luminosity functions in $^{0.1}u$, $^{0.1}g$, $^{0.1}r$, $^{0.1}i$ and $^{0.1}z$ bands agree quite well with the SDSS observational results down to an absolute magnitude at about -17.0. The SDSS conditional luminosity functions (CLF) itself is predicted well. Finally, the cold gas is derived from the star formation rate (SFR) to predict the HI gas mass within each mock galaxy. We find a remarkably good match to observed HI-to-stellar mass ratios. These features ensure that such galaxy/gas catalogs can be used to generate reliable mock redshift surveys.