Nonlinear corrections to the cosmological matter power spectrum and scale-dependent galaxy bias: implications for parameter estimation

TL;DR

This paper compares two nonlinear correction models for galaxy power spectrum analysis, highlighting the P model's robustness and physical transparency over the Q model, especially in complex cosmologies with relic particles.

Contribution

The paper introduces and evaluates the P model based on the halo model, demonstrating its advantages over the traditional Q model in complex cosmological scenarios.

Findings

Both models perform well in standard cosmology.

The Q model can give unphysical results with relic thermal axions.

The P model remains stable and physically transparent in complex scenarios.

Abstract

We explore and compare the performances of two nonlinear correction and scale-dependent biasing models for the extraction of cosmological information from galaxy power spectrum data, especially in the context of beyond-LCDM cosmologies. The first model is the well known Q model, first applied in the analysis of 2dFGRS data. The second, the P model, is inspired by the halo model, in which nonlinear evolution and scale-dependent biasing are encapsulated in a single non-Poisson shot noise term. We find that while both models perform equally well in providing adequate correction for a range of galaxy clustering data in standard LCDM cosmology and in extensions with massive neutrinos, the Q model can give unphysical results in cosmologies containing a subdominant free-streaming dark matter whose temperature depends on the particle mass, e.g., relic thermal axions, unless a suitable prior is imposed on the correction parameter. This last case also exposes the danger of analytic marginalisation, a technique sometimes used in the marginalisation of nuisance parameters. In contrast, the P model suffers no undesirable effects, and is the recommended nonlinear correction model also because of its physical transparency.