Biased tracers as a probe of beyond-$\Lambda$CDM cosmologies

TL;DR

This paper examines how the selection of biased tracers influences the detection of signatures of beyond-$ Lambda$CDM cosmologies in large-scale structure, emphasizing the importance of bias modeling for accurate cosmological constraints.

Contribution

It demonstrates that selecting tracers at fixed bias recovers the cosmological signals lost with mass-based selection, highlighting the importance of bias modeling in cosmological analyses.

Findings

Mass-based tracer selection diminishes the observable signals.

Fixed bias selection recovers the full cosmological signatures.

Accurate bias modeling is crucial for constraining beyond-$ Lambda$CDM models.

Abstract

Cosmological models beyond $\Lambda$CDM, like those featuring massive neutrinos or modifications of gravity, often display a characteristic change (scale-dependent suppression or enhancement) in the matter power spectrum when compared to a $\Lambda$CDM baseline. It is therefore a widely held view that constraints on those models can be obtained by searching for such features in the clustering statistics of large-scale structure. However, when using biased tracers of matter in the analysis, the situation is complicated by the fact that the bias also depends on cosmology. Here we investigate how the selection of tracers affects the observed signatures for two examples of beyond-$\Lambda$CDM cosmologies: massive neutrinos and clustering dark energy ($k$-essence). We study the signatures in the monopole, quadrupole, and hexadecapole of the redshift-space power spectra for halo catalogues from large $N$-body simulations and argue that a fixed selection criterion based on local attributes like tracer mass leads to a near loss of signal in most cases. Instead, the full signal is recovered only if the selection of tracers is done at fixed bias. This emphasises the need to model or measure the bias parameters accurately in order to get meaningful constraints on the cosmological model.