Triumvirate: A Python/C++ package for three-point clustering measurements

TL;DR

Triumvirate is a versatile Python/C++ package designed for efficient measurement of three-point clustering statistics in large-scale structure analyses, facilitating cosmological model testing with user-friendly features.

Contribution

It introduces an end-to-end, configurable tool for three-point clustering measurements based on advanced algorithms, with integrated two-point statistics for comprehensive analysis.

Findings

Provides efficient estimators for three-point correlation functions.

Includes flexible I/O and user-friendly interface.

Supports both three-point and two-point clustering measurements.

Abstract

Triumvirate is a Python/C++ package for measuring the three-point clustering statistics in large-scale structure (LSS) cosmological analyses. Given a catalogue of discrete particles (such as galaxies) with their spatial coordinates, it computes estimators of the multipoles of the three-point correlation function, also known as the bispectrum in Fourier space, in the tri-polar spherical harmonic (TripoSH) decomposition proposed by Sugiyama et al. (2019). The objective of Triumvirate is to provide efficient end-to-end measurement of clustering statistics which can be fed into downstream galaxy survey analyses to constrain and test cosmological models. To this end, it builds upon the original algorithms in the hitomi code developed by Sugiyama et al. (2018, 2019), and supplies a user-friendly interface with flexible input/output (I/O) of catalogue data and measurement results, with the built program configurable through external parameter files and tracked through enhanced logging and warning/exception handling. For completeness and complementarity, methods for measuring two-point clustering statistics are also included in the package.