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arXiv · 2409.14143

GWPopulation: Hardware agnostic population inference for compact binaries and beyond

Colm Talbot·Amanda Farah·Shanika Galaudage·Jacob Golomb·Hui Tong
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Abstract

Since the first direct detection of gravitational waves by the LIGO--Virgo collaboration in 2015, the size of the gravitational-wave transient catalog has grown to nearly 100 events, with more than as many observed during the ongoing fourth observing run. Extracting astrophysical/cosmological information from these observations is a hierarchical Bayesian inference problem. GWPopulation is designed to provide simple-to-use, robust, and extensible tools for hierarchical inference in gravitational-wave astronomy/cosmology. It has been widely adopted for gravitational-wave astronomy, including producing flagship results for the LIGO-Virgo-KAGRA collaborations. While designed to work with observations of compact binary coalescences, GWPopulation may be available to a wider range of hierarchical Bayesian inference problems.

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Colm Talbot, Amanda Farah, Shanika Galaudage, Jacob Golomb, Hui Tong. 2024-09-21. GWPopulation: Hardware agnostic population inference for compact binaries and beyond. https://arxiv.org/abs/2409.14143

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