Modeling features in the redshift-space halo power spectrum with perturbation theory

TL;DR

This paper demonstrates that perturbation theory models, including effective field theory and infra-red resummation, can accurately predict the redshift-space clustering of biased tracers in models with primordial features, aligning well with large N-body simulations.

Contribution

It is the first to show that perturbative models can accurately fit the redshift-space clustering in models with features in the linear power spectrum.

Findings

Perturbation theory models match N-body simulations up to non-linear scales.

Different IR resummation schemes are compared to assess theoretical uncertainties.

Future surveys can detect primordial features below 1% level across scales.

Abstract

We study the ability of perturbative models with effective field theory contributions and infra-red resummation to model the redshift space clustering of biased tracers in models where the linear power spectrum has "features" -- either imprinted during inflation or induced by non-standard expansion histories. We show that both Eulerian and Lagrangian perturbation theory are capable of reproducing the Fourier space two-point functions of halos up to the non-linear scale from a suite of $4096^3$ particle N-body simulations. This is the first demonstration that perturbative models can accurately fit the redshift-space clustering of biased tracers in N-body simulations of such theories. By comparing different theoretical models and IR resummation schemes we assess the current theoretical uncertainty in predicting power spectra for models with features. Our results suggest that future surveys will be able to detect or tightly constrain features in the primordial spectrum below the one percent level across a wide range of scales.