Improved Mock Galaxy Catalogs for the DEEP2 Galaxy Redshift Survey from Subhalo Abundance and Environment Matching

TL;DR

This paper presents new empirical mock galaxy catalogs for the DEEP2 survey, using subhalo abundance matching and environment-dependent color assignment, to improve modeling of galaxy properties in cosmological simulations.

Contribution

The authors develop a novel method combining subhalo abundance matching with environment-based color assignment to produce realistic mock galaxy catalogs for DEEP2.

Findings

No constant scatter model reproduces both luminosity function and autocorrelation.

Mocks accurately reproduce multiple observed galaxy properties.

Results inform galaxy formation models and mock catalog applications.

Abstract

We develop empirical methods for modeling the galaxy population and populating cosmological N-body simulations with mock galaxies according to the observed properties of galaxies in survey data. We use these techniques to produce a new set of mock catalogs for the DEEP2 Galaxy Redshift Survey based on the output of the high-resolution Bolshoi simulation, as well as two other simulations with different cosmological parameters, all of which we release for public use. The mock-catalog creation technique uses subhalo abundance matching to assign galaxy luminosities to simulated dark-matter halos. It then adds color information to the resulting mock galaxies in a manner that depends on the local galaxy density, in order to reproduce the measured color-environment relation in the data. In the course of constructing the catalogs, we test various models for including scatter in the relation between halo mass and galaxy luminosity, within the abundance-matching framework. We find that there is no constant-scatter model that can simultaneously reproduce both the luminosity function and the autocorrelation function of DEEP2. This result has implications for galaxy-formation theory, and it restricts the range of contexts in which the mocks can be usefully applied. Nevertheless, careful comparisons show that our new mocks accurately reproduce a wide range of the other properties of the DEEP2 catalog, suggesting that they can be used to gain a detailed understanding of various selection effects in DEEP2.