Impacts of biasing schemes in the one-loop integrated perturbation theory

TL;DR

This paper analytically examines how different biasing schemes influence the clustering of large-scale structure tracers in the weakly nonlinear regime using one-loop integrated perturbation theory, highlighting model-dependent effects.

Contribution

It introduces formulae for renormalized bias functions across various physically motivated Lagrangian bias schemes within the one-loop integrated perturbation theory framework.

Findings

Bias models cause a few percent variation in power spectra and correlation functions.

Scale-dependent bias amplitude is affected by primordial non-Gaussianity and bias model details.

Theoretical uncertainties in bias modeling can impact cosmological parameter constraints.

Abstract

The impact of biasing schemes on the clustering of tracers of the large-scale structure is analytically studied in the weakly nonlinear regime. For this purpose, we use the one-loop approximation of the integrated perturbation theory together with the renormalized bias functions of various, physically motivated Lagrangian bias schemes. These include the halo, peaks and excursion set peaks model, for which we derive useful formulae for the evaluation of their renormalized bias functions. The shapes of the power spectra and correlation functions are affected by the different bias models at the level of a few percent on weakly nonlinear scales. These effects are studied quantitatively both in real and redshift space. The amplitude of the scale-dependent bias in the presence of primordial non-Gaussianity also depends on the details of the bias models. If left unaccounted for, these theoretical uncertainties could affect the robustness of the cosmological constraints extracted from galaxy clustering data.