Luminosity bias: from haloes to galaxies

TL;DR

This paper reviews how galaxy clustering bias, influenced by galaxy properties, affects cosmological measurements and discusses empirical and physical modeling approaches to understand this bias.

Contribution

It provides a comprehensive review of galaxy bias modeling, comparing empirical and physics-based methods and summarizing current understanding.

Findings

Galaxy bias varies with galaxy properties like luminosity and color.

Empirical models adjust dark matter distributions to match observations.

Physics-based models aim to predict galaxy distribution from baryonic physics.

Abstract

Large surveys of the local Universe have shown that galaxies with different intrinsic properties, such as colour, luminosity and morphological type display a range of clustering amplitudes. Galaxies are therefore not faithful tracers of the underlying matter distribution. This modulation of galaxy clustering, called bias, contains information about the physics behind galaxy formation. It is also a systematic to be overcome before the large-scale structure of the Universe can be used as a cosmological probe. Two types of approaches have been developed to model the clustering of galaxies. The first class is empirical and filters or weights the distribution of dark matter to reproduce the measured clustering. In the second approach an attempt is made to model the physics which governs fate of baryons in order to predict the number of galaxies in dark matter haloes. I will review the development of both approaches and summarize what we have learnt about galaxy bias.