Unveiling Galaxy Bias via the Halo Model, KiDS and GAMA
Andrej Dvornik, Konrad Kuijken, Henk Hoekstra, Peter Schneider,, Alexandra Amon, Reiko Nakajima, Massimo Viola, Ami Choi, Thomas Erben, Daniel, J. Farrow, Catherine Heymans, Hendrik Hildebrandt, Crist\'obal Sif\'on,, Lingyu Wang

TL;DR
This study uses galaxy clustering and lensing data from GAMA and KiDS to analyze galaxy bias through halo occupation models, revealing the physical origins of non-linearity and stochasticity in galaxy biasing.
Contribution
It provides a detailed analysis of galaxy bias using halo occupation statistics, connecting observational signals with the physical processes in dark matter haloes.
Findings
Stochasticity mainly from non-Poissonian satellite galaxy distribution.
Non-linearity primarily due to central galaxies.
More massive galaxies show stronger scale dependence.
Abstract
We measure the projected galaxy clustering and galaxy-galaxy lensing signals using the Galaxy 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 , where is the projected comoving separation, is evaluated using the analytical halo model from which the scale dependence of , 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…
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