A Computationally Efficient Approach for Calculating Galaxy Two-Point Correlations

TL;DR

This paper presents a new computational method for calculating galaxy two-point correlations that is faster and more precise, enabling efficient exploration of cosmological parameters in large-scale structure analysis.

Contribution

The authors introduce a modified estimator that replaces pairwise calculations with fast integrations, significantly improving speed and accuracy in galaxy correlation computations.

Findings

Reduces computation time for correlation functions

Increases precision of galaxy clustering measurements

Facilitates efficient exploration of cosmological parameters

Abstract

We developed a modification to the calculation of the two-point correlation function commonly used in the analysis of large scale structure in cosmology. An estimator of the two-point correlation function is constructed by contrasting the observed distribution of galaxies with that of a uniformly populated random catalog. Using the assumption that the distribution of random galaxies in redshift is independent of angular position allows us to replace pairwise combinatorics with fast integration over probability maps. The new method significantly reduces the computation time while simultaneously increasing the precision of the calculation. It also allows to introduce cosmological parameters only at the last and least computationally expensive stage, which is helpful when exploring various choices for these parameters.