On Combining Galaxy Clustering and Weak Lensing to Unveil Galaxy Biasing via the Halo Model
Marcello Cacciato, Ofer Lahav, Frank C. van den Bosch, Henk Hoekstra,, Avishai Dekel

TL;DR
This paper models non-linear and stochastic galaxy biasing using the halo model, proposing a combined analysis of galaxy clustering and weak lensing to better understand galaxy bias properties across different scales.
Contribution
It introduces the bias function Gamma_{gm}(r_p) combining clustering and lensing data, enabling observational constraints on galaxy biasing and halo occupation parameters.
Findings
Galaxy bias becomes scale-independent beyond 1-5 Mpc/h in real-space.
Projected bias functions reveal detailed information about galaxy biasing.
Brighter galaxies show stronger and larger-scale bias dependence.
Abstract
We formulate the concept of non-linear and stochastic galaxy biasing in the framework of halo occupation statistics. Using two-point statistics in projection, we define the galaxy bias function, b_g(r_p), and the galaxy-dark matter cross-correlation function, R_{gm}(r_p), where r_p is the projected distance. We use the analytical halo model to predict how the scale dependence of b_g and R_{gm}, over the range 0.1 Mpc/h < r_p < 30 Mpc/h, depends on the non-linearity and stochasticity in halo occupation models. In particular we quantify the effect due to the presence of central galaxies, the assumption for the radial distribution of satellite galaxies, the richness of the halo, and the Poisson character of the probability to have a certain number of satellite galaxies in a halo of a certain mass. Overall, brighter galaxies reveal a stronger scale dependence, and out to a larger radius. In…
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