# Extending the modeling of the anisotropic galaxy power spectrum to $k = 0.4 \ h\mathrm{Mpc}^{-1}$

## TL;DR

This paper introduces a new, physically motivated model for the galaxy redshift-space power spectrum that accurately extends to smaller scales of $k=0.4 \, h\mathrm{Mpc}^{-1}$, improving precision in cosmological parameter estimation.

## Contribution

The paper develops a novel galaxy power spectrum model combining halo modeling, perturbation theory, and simulations, with 13 physical parameters, validated on diverse simulations and mock catalogs.

## Key findings

- Model accurately fits monopole, quadrupole, and hexadecapole down to $k=0.4 \, h\mathrm{Mpc}^{-1}$.
- Including smaller scales yields 15-30 ext% improvements in $f\sigma_8$ precision.
- Bias in $f\sigma_8$ recovery is small across tested simulations.

## Abstract

We present a new model for the redshift-space power spectrum of galaxies and demonstrate its accuracy in modeling the monopole, quadrupole, and hexadecapole of the galaxy density field down to scales of $k = 0.4 \ h\mathrm{Mpc}^{-1}$. The model describes the clustering of galaxies in the context of a halo model and the clustering of the underlying halos in redshift space using a combination of Eulerian perturbation theory and $N$-body simulations. The modeling of redshift-space distortions is done using the so-called distribution function approach. The final model has 13 free parameters, and each parameter is physically motivated rather than a nuisance parameter, which allows the use of well-motivated priors. We account for the Finger-of-God effect from centrals and both isolated and non-isolated satellites rather than using a single velocity dispersion to describe the combined effect. We test and validate the accuracy of the model on several sets of high-fidelity $N$-body simulations, as well as realistic mock catalogs designed to simulate the BOSS DR12 CMASS data set. The suite of simulations covers a range of cosmologies and galaxy bias models, providing a rigorous test of the level of theoretical systematics present in the model. The level of bias in the recovered values of $f \sigma_8$ is found to be small. When including scales to $k = 0.4 \ h\mathrm{Mpc}^{-1}$, we find 15-30\% gains in the statistical precision of $f \sigma_8$ relative to $k = 0.2 \ h\mathrm{Mpc}^{-1}$ and a roughly 10-15\% improvement for the perpendicular Alcock-Paczynski parameter $\alpha_\perp$. Using the BOSS DR12 CMASS mocks as a benchmark for comparison, we estimate an uncertainty on $f \sigma_8$ that is $\sim$10-20\% larger than other similar Fourier-space RSD models in the literature that use $k \leq 0.2 \ h\mathrm{Mpc}^{-1}$, suggesting that these models likely have a too-limited parametrization.