Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-55340
Leauthaud, A; Tinker, J; Behroozi, P S; Busha, M T; Wechsler, R (2011). A theoretical framework for combining techniques that probe the link between galaxies and dark matter. Astrophysical Journal, 738(1):45.
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We develop a theoretical framework that combines measurements of galaxy-galaxy lensing, galaxy clustering, and the galaxy stellar mass function in a self-consistent manner. While considerable effort has been invested in exploring each of these probes individually, attempts to combine them are still in their infancy. These combinations have the potential to elucidate the galaxy-dark matter connection and the galaxy formation physics responsible for it, as well as to constrain cosmological parameters and to test the nature of gravity. In this paper, we focus on a theoretical model that describes the galaxy-dark matter connection based on standard halo occupation distribution techniques. Several key modifications enable us to extract additional parameters that determine the stellar-to-halo mass relation and to simultaneously fit data from multiple probes while allowing for independent binning schemes for each probe. We construct mock catalogs from numerical simulations to investigate the effects of sample variance and covariance for each probe. Finally, we analyze how trends in each of the three observables impact the derived parameters of the model. In particular, we investigate various features of the observed galaxy stellar mass function (low-mass slope, "plateau," knee, and high-mass cutoff) and show how each feature is related to the underlying relationship between stellar and halo mass. We demonstrate that the observed "plateau" feature in the stellar mass function at M * ~ 2 × 1010 M sun is due to the transition that occurs in the stellar-to-halo mass relation at Mh ~ 1012 M sun from a low-mass power-law regime to a sub-exponential function at higher stellar mass.
|Item Type:||Journal Article, refereed, original work|
|Communities & Collections:||07 Faculty of Science > Institute for Computational Science|
|Deposited On:||18 Feb 2012 09:58|
|Last Modified:||16 Jun 2014 12:04|
|ISSN:||0004-637X (P) 1538-4357 (E)|
|Citations:||Web of Science®. Times Cited: 31|
Scopus®. Citation Count: 21
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