Cosmology inference at the field level from biased tracers in redshift-space

TL;DR

This paper extends a cosmological inference pipeline to redshift space, demonstrating unbiased growth rate constraints and velocity bias detection from galaxy clustering data using an EFT likelihood approach.

Contribution

The work introduces a systematic expansion of velocity bias and applies the pipeline to various synthetic data, achieving accurate growth rate inference and velocity bias detection.

Findings

Unbiased growth rate constraints within a few percent across halo masses and redshifts.

Detection of velocity bias effects in redshift-space clustering.

Validation of the pipeline on synthetic data with known ground truth.

Abstract

Cosmology inference of galaxy clustering at the field level with the EFT likelihood in principle allows for extracting all non-Gaussian information from quasi-linear scales, while robustly marginalizing over any astrophysical uncertainties. A pipeline in this spirit is implemented in the \texttt{LEFTfield} code, which we extend in this work to describe the clustering of galaxies in redshift space. Our main additions are: the computation of the velocity field in the LPT gravity model, the fully nonlinear displacement of the evolved, biased density field to redshift space, and a systematic expansion of velocity bias. We test the resulting analysis pipeline by applying it to synthetic data sets with a known ground truth at increasing complexity: mock data generated from the perturbative forward model itself, sub-sampled matter particles, and dark matter halos in N-body simulations. By fixing the initial-time density contrast to the ground truth, while varying the growth rate $f$, bias coefficients and noise amplitudes, we perform a stringent set of checks. These show that indeed a systematic higher-order expansion of the velocity bias is required to infer a growth rate consistent with the ground truth within errors. Applied to dark matter halos, our analysis yields unbiased constraints on $f$ at the level of a few percent for a variety of halo masses at redshifts $z=0,\,0.5,\,1$ and for a broad range of cutoff scales $0.08\,h/\mathrm{Mpc} \leq \Lambda \leq 0.20\,h/\mathrm{Mpc}$. Importantly, deviations between true and inferred growth rate exhibit the scaling with halo mass, redshift and cutoff that one expects based on the EFT of Large Scale Structure. Further, we obtain a robust detection of velocity bias through its effect on the redshift-space density field and are able to disentangle it from higher-derivative bias contributions.