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

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 $0.08h/\mathrm{Mpc}\le \Lambda \le 0.20h/\mathrm{Mpc}$. 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.

References in corpus (9)

• The Effective Field Theory of Cosmological Large Scale Structures
• Resumming Cosmological Perturbations via the Lagrangian Picture: One-loop Results in Real Space and in Redshift Space
• Cosmology with the SPHEREX All-Sky Spectral Survey
• ELUCID - Exploring the Local Universe with reConstructed Initial Density field I: Hamiltonian Markov Chain Monte Carlo Method with Particle Mesh Dynamics
• Redshift-Space Distortions in Lagrangian Perturbation Theory
• The Gaussian streaming model and Lagrangian effective field theory
• Baryon acoustic signature in the clustering of density maxima
• Galaxy peculiar velocities and evolution-bias
• Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

Cited by in corpus (12)

• How much information can be extracted from galaxy clustering at the field level?
• A Parameter-Masked Mock Data Challenge for Beyond-Two-Point Galaxy Clustering Statistics
• EFTofLSS meets simulation-based inference: ${\sigma }_8$ from biased tracers
• Bayesian Inference of Initial Conditions from Non-Linear Cosmic Structures using Field-Level Emulators
• Accurate field-level weak lensing inference for precision cosmology
• Straightening the Ruler: Field-Level Inference of the BAO Scale with LEFTfield
• Calculating the EFT likelihood via saddle-point expansion
• Bye-bye, Local-in-matter-density Bias: The Statistics of the Halo Field Are Poorly Determined by the Local Mass Density
• Perturbation Theory Remixed II: Improved Modeling of Nonlinear Bispectrum
• The Manticore Project II: Bayesian digital twins of cosmic structure across the SDSS and BOSS volumes
• Emulating galaxy and peculiar velocity clustering on non-linear scales
• Differentiable Fuzzy Cosmic-Web for Field Level Inference