Unveiling galaxy bias via the halo model, KiDS, and GAMA

Andrej Dvornik, Henk Hoekstra, Konrad Kuijken, Peter Schneider, Alexandra Amon, Reiko Nakajima, Massimo Viola, Ami Choi, Thomas Erben, Daniel J. Farrow, Catherine Heymans, Hendrik Hildebrandt, Cristóbal Sifón, Lingyu Wang

Research output: Contribution to journalArticlepeer-review

36 Scopus citations


We measure the projected galaxy clustering and galaxy-galaxy lensing signals using theGalaxy And Mass Assembly (GAMA) survey and Kilo-Degree Survey (KiDS) to study galaxy bias. We use the concept of non-linear and stochastic galaxy biasing in the framework of halo occupation statistics to constrain the parameters of the halo occupation statistics and to unveil the origin of galaxy biasing. The bias function Γgm(rp), where rp is the projected comoving separation, is evaluated using the analytical halo model from which the scale dependence of Γgm(rp), and the origin of the non-linearity and stochasticity in halo occupation models can be inferred. Our observations unveil the physical reason for the non-linearity and stochasticity, further explored using hydrodynamical simulations, with the stochasticity mostly originating from the non-Poissonian behaviour of satellite galaxies in the dark matter haloes and their spatial distribution, which does not follow the spatial distribution of dark matter in the halo. The observed non-linearity is mostly due to the presence of the central galaxies, as was noted from previous theoretical work on the same topic. We also see that overall, more massive galaxies reveal a stronger scale dependence, and out to a larger radius. Our results show that a wealth of information about galaxy bias is hidden in halo occupation models. These models should therefore be used to determine the influence of galaxy bias in cosmological studies.

Original languageEnglish (US)
Pages (from-to)1240-1259
Number of pages20
JournalMonthly Notices of the Royal Astronomical Society
Issue number1
StatePublished - Sep 1 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science


  • Dark matter
  • Galaxies: haloes
  • Gravitational lensing: weak
  • Large-scale structure of Universe
  • Methods: statistical
  • Surveys


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