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Title: Improved Mock Galaxy Catalogs for the Deep2 Galaxy Redshift Survey From Subhalo Abundance and Environment Matching

Journal Article · · Astrophysical Journal, Supplement Series
 [1];  [2];  [2];  [3];  [4];  [5]
  1. SLAC National Accelerator Lab., Menlo Park, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. SLAC National Accelerator Lab., Menlo Park, CA (United States); Stanford Univ., CA (United States)
  3. Univ. of California, Irvine, CA (United States)
  4. New York Univ. (NYU), NY (United States)
  5. Univ. of California, San Diego, CA (United States)
+ Show Author Affiliations

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. Finally, this result has implications for galaxy-formation theory, and it restricts the range of contexts in which the mock catalogs can be usefully applied. Nevertheless, careful comparisons show that our new mock catalogs 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.

Research Organization:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
AC02-76SF00515
OSTI ID:
1443142
Report Number(s):
SLAC-PUB-14493
Journal Information:
Astrophysical Journal, Supplement Series, Vol. 208, Issue 1; ISSN 0067-0049
Publisher:
American Astronomical SocietyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 14 works
Citation information provided by
Web of Science

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