The Anisotropic Line Correlation Function as a Probe of Anisotropies in Galaxy Surveys

TL;DR

This paper introduces an anisotropic line correlation function (ALCF) to analyze phase information in galaxy large-scale structures, effectively capturing non-linear features and anisotropies, and demonstrating its potential to measure cosmological effects like the Alcock-Paczynski effect.

Contribution

The paper develops and tests an anisotropic extension of the line correlation function, providing a new tool for probing non-linear structure and anisotropies in galaxy surveys.

Findings

ALCF effectively captures anisotropies in galaxy distributions.

ALCF can measure the Alcock-Paczynski effect.

ALCF is robust against linear bias and Gaussian variance.

Abstract

We propose an anisotropic generalisation of the line correlation function (ALCF) to separate and quantify phase information in the large-scale structure of galaxies. The line correlation function probes the strictly non-linear regime of structure formation and since phase information drops out of the power spectrum, the line correlation function provides a complementary tool to commonly used techniques based on two-point statistics. Furthermore, it is independent of linear bias as well as the Gaussian variance on the modulus of the density field and thus may also prove to be advantageous compared to the bispectrum or similar higher-order statistics for certain cases. For future applications it is vital, though, to be able to account for observational effects that cause anisotropies in the distribution of galaxies. Based on a number of numerical studies, we find that our ALCF is well suited to accomplish this task and we demonstrate how the Alcock-Paczynski effect and kinematical redshift-space distortions can in principle be measured via the ALCF.