Connecting Massive Galaxies to Dark Matter Haloes in BOSS - I. Is Galaxy Colour a Stochastic Process in High-Mass Haloes?
Abstract
We use subhalo abundance matching (SHAM) to model the stellar mass function (SMF) and clustering of the Baryon Oscillation Spectroscopic Survey (BOSS) 'CMASS' sample at z ~ 0.5. We introduce a novel method which accounts for the stellar mass incompleteness of CMASS as a function of redshift, and produce CMASS mock catalogues which include selection effects, reproduce the overall SMF, the projected two-point correlation function wp, the CMASS dn/dz, and are made publicly available. We study the effects of assembly bias above collapse mass in the context of 'age matching' and show that these effects are markedly different compared to the ones explored by Hearin et al. at lower stellar masses. We construct two models, one in which galaxy colour is stochastic ('AbM' model) as well as a model which contains assembly bias effects ('AgM' model). By confronting the redshift dependent clustering of CMASS with the predictions from our model, we argue that that galaxy colours are not a stochastic process in high-mass haloes. Our results suggest that the colours of galaxies in high-mass haloes are determined by other halo properties besides halo peak velocity and that assembly bias effects play an important role in determining the clustering properties of this sample.
Recommended Citation
S. Saito et al., "Connecting Massive Galaxies to Dark Matter Haloes in BOSS - I. Is Galaxy Colour a Stochastic Process in High-Mass Haloes?," Monthly Notices of the Royal Astronomical Society, vol. 460, no. 2, pp. 1457 - 1475, Oxford University Press, Aug 2016.
The definitive version is available at https://doi.org/10.1093/mnras/stw1080
Department(s)
Physics
Keywords and Phrases
Galaxies: haloes; Large-scale structure of Universe
International Standard Serial Number (ISSN)
0035-8711; 1365-2966
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2016 The Authors, All rights reserved.
Publication Date
01 Aug 2016