4.7 Article

Scale-dependent galaxy bias in the Sloan Digital Sky Survey as a function of luminosity and colour

期刊

出版社

OXFORD UNIV PRESS
DOI: 10.1111/j.1365-2966.2008.14082.x

关键词

methods: statistical; galaxies: evolution; galaxies: luminosity function, mass function; galaxies: statistics; cosmology: observations; large-scale structure of Universe

资金

  1. STFC PhD studentship
  2. Leverhulme Trust
  3. European Research Council
  4. STFC [PP/E001033/1, ST/F002335/1] Funding Source: UKRI
  5. Science and Technology Facilities Council [PP/E001033/1, ST/F002335/1, PP/C50613X/1] Funding Source: researchfish

向作者/读者索取更多资源

It has been known for a long time that the clustering of galaxies changes as a function of galaxy type. This galaxy bias acts as a hindrance to the extraction of cosmological information from the galaxy power spectrum or correlation function. Theoretical arguments show that a change in the amplitude of the clustering between galaxies and mass on large scales is unavoidable, but cosmological information can be easily extracted from the shape of the power spectrum or correlation function if this bias is independent of scale. Scale-dependent bias is generally small on large scales, k < 0.1 h Mpc(-1), but on smaller scales can affect the recovery of Omega(m)h from the measured shape of the clustering signal, and have a small effect on the Baryon Acoustic Oscillations. In this paper, we investigate the transition from scale-independent to scale-dependent galaxy bias as a function of galaxy population. We use the Sloan Digital Sky Survey Data Release 5 sample to fit various models, which attempt to parametrize the turn-off from scale-independent behaviour. For blue galaxies, we find that the strength of the turn-off is strongly dependent on galaxy luminosity, with stronger scale-dependent bias on larger scales for more luminous galaxies. For red galaxies, the scale dependence is a weaker function of luminosity. Such trends need to be modelled in order to optimally extract the information available in future surveys, and can help with the design of such surveys.

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