Multi-wavelength consensus of large-scale linear bias

TL;DR

This paper models the large-scale linear galaxy bias across multiple wavelengths and emission lines using semi-analytic galaxy formation models, providing a versatile fitting formula for survey applications.

Contribution

It introduces a five-parameter model for galaxy bias as a function of magnitude, redshift, and wavelength, validated against observations and applicable to various survey types.

Findings

Bias can be modeled with a unified five-parameter formula.

Continuum band biases are similar across wavelengths due to galaxy mixing.

The model shows reasonable agreement with observational data within uncertainties.

Abstract

We model the large-scale linear galaxy bias $b_g(x,z)$ as a function of redshift $z$ and observed absolute magnitude threshold $x$ for broadband continuum emission from the far infrared to ultra-violet, as well as for prominent emission lines, such as the H$\alpha$, H$\beta$, Lya and [OII] lines. The modelling relies on the semi-analytic galaxy formation model GALFORM, run on the state-of-the-art $N$-body simulation SURFS with the Planck 2015 cosmology. We find that both the differential bias at observed absolute magnitude $x$ and the cumulative bias for magnitudes brighter than $x$ can be fitted with a five-parameter model: $b_g(x,z)=a + b(1+z)^e(1 + \exp{[(x-c)d]})$. We also find that the bias for the continuum bands follows a very similar form regardless of wavelength due to the mixing of star-forming and quiescent galaxies in a magnitude limited survey. Differences in bias only become apparent when an additional colour separation is included, which suggest extensions to this work could look at different colours at fixed magnitude limits. We test our fitting formula against observations, finding reasonable agreement with some measurements within $1\sigma$ statistical uncertainties, and highlighting areas of improvement. We provide the fitting parameters for various continuum bands, emission lines and intrinsic galaxy properties, enabling a quick estimation of the linear bias in any typical survey of large-scale structure.