Triumvirate: A Python/C++ package for three-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.

arXiv comment6 pages, 1 table. Accepted by JOSS: added references and performance details; new code release v0.3.0. Code available at https://github.com/MikeSWang/Triumvirate

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Cited by in corpus (4)

• Window convolution of the galaxy clustering bispectrum
• Modelling the covariance matrix for the power spectra before and after the BAO reconstruction
• Modeling and measuring the anisotropic halo 3-point correlation function: a coordinated study
• Web-Halo Model (WHM): Accurate non-linear matter power spectrum predictions without free parameters