A Practical Computational Method for the Anisotropic Redshift-Space 3-Point Correlation Function

TL;DR

This paper introduces an efficient algorithm to compute the anisotropic redshift-space galaxy 3-point correlation function, enabling detailed analysis of redshift-space distortions in large-scale surveys with minimal additional computational cost.

Contribution

The authors generalize previous isotropic 3PCF methods to include anisotropy due to redshift-space distortions, providing a scalable, exact, and practical computational approach.

Findings

Algorithm scales as N^2 for large datasets

Provides the covariance matrix for the anisotropic 3PCF

Tracks the full 5-D redshift-space 3PCF with edge correction

Abstract

We present an algorithm enabling computation of the anisotropic redshift-space galaxy 3-point correlation function (3PCF) scaling as $N^2$, with $N$ the number of galaxies. Our previous work showed how to compute the isotropic 3PCF with this scaling by expanding the radially-binned density field around each galaxy in the survey into spherical harmonics and combining these coefficients to form multipole moments. The $N^2$ scaling occurred because this approach never explicitly required the relative angle between a galaxy pair about the primary galaxy. Here we generalize this work, demonstrating that in the presence of azimuthally-symmetric anisotropy produced by redshift-space distortions (RSD) the 3PCF can be described by two triangle side lengths, two independent total angular momenta, and a spin. This basis for the anisotropic 3PCF allows its computation with negligible additional work over the isotropic 3PCF. We also present the covariance matrix of the anisotropic 3PCF measured in this basis. Our algorithm tracks the full 5-D redshift-space 3PCF, uses an accurate line of sight to each triplet, is exact in angle, and easily handles edge correction. It will enable use of the anisotropic large-scale 3PCF as a probe of RSD in current and upcoming large-scale redshift surveys.