# Alcock-Paczynski Test with the Evolution of Redshift-Space Galaxy Clustering Anisotropy

## TL;DR

This paper presents an improved Alcock-Paczynski test using the redshift-space two-point correlation function of galaxies, enhancing cosmological constraints by accounting for non-linear evolution and utilizing full 2D shape information.

## Contribution

The authors develop a 2D fitting scheme for the correlation function that improves constraints on cosmological parameters and incorporates non-linear evolution effects.

## Key findings

- Tightens constraints on $\
- accounts for non-linear evolution dependence on cosmology

## Abstract

We develop an improved Alcock-Paczynski (AP) test method that uses the redshift-space two-point correlation function (2pCF) of galaxies. Cosmological constraints can be obtained by examining the redshift dependence of the normalized 2pCF, which should not change apart from the expected small non-linear evolution. An incorrect choice of cosmology used to convert redshift to comoving distance will manifest itself as redshift-dependent 2pCF. Our method decomposes the redshift difference of the two-dimensional correlation function into the Legendre polynomials whose amplitudes are modeled by radial fitting functions. Our likelihood analysis with this 2-D fitting scheme tightens the constraints on $\Omega_m$ and ${w}$ by $\sim 40\%$ compared to the method of Li et al. (2016, 2017, 2018) that uses one dimensional angular dependence only. We also find that the correction for the non-linear evolution in the 2pCF has a non-negligible cosmology dependence, which has been neglected in previous similar studies by Li et al.. With an accurate accounting for the non-linear systematics and use of full two-dimensional shape information of the 2pCF down to scales as small as $5~h^{-1}{\rm Mpc}$ it is expected that the AP test with redshift-space galaxy clustering anisotropy can be a powerful method to constrain the expansion history of the universe.