부산대학교 도서관

Dark matter simulations can serve as a basis for creating galaxy histories via the galaxy-dark matter connection. Here, one such model by Becker (2015) is implemented with several variations on three different dark matter simulations. Stellar mass and star formation rates are assigned to all simulation subhalos at all times, using subhalo mass gain to determine stellar mass gain. The observational properties of the resulting galaxy distributions are compared to each other and observations for a range of redshifts from 0-2. Although many of the galaxy distributions seem reasonable, there are noticeable differences as simulations, subhalo mass gain definitions, or subhalo mass definitions are altered, suggesting that the model should change as these properties are varied. Agreement with observations may improve by including redshift dependence in the added-by-hand random contribution to star formation rate. There appears to be an excess of faint quiescent galaxies as well (perhaps due in part to differing definitions of quiescence). The ensemble of galaxy formation histories for these models tend to have more scatter around their average histories (for a fixed final stellar mass) than the two more predictive and elaborate semi-analytic models of Guo et al (2013) and Henriques et al (2015), and require more basis fluctuations (using PCA) to capture 90 percent of the scatter around their average histories. The codes to plot model predictions (in some cases alongside observational data) are publicly available to test other mock catalogues at https://github.com/jdcphysics/validation . Information on how to use these codes is in the appendix.
Comment: Paper also serves as documentation for public code validating mock catalogues which have M*, star formation rates, stellar mass to halo mass information (redshifts 0 to ~ 4, most data sets for 0 to 2)