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GWPopulation: Hardware agnostic population inference for compact binaries and beyond

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arxiv 2409.14143 v1 pith:BF67SNBO submitted 2024-09-21 astro-ph.IM gr-qc

Colm Talbot , Amanda Farah , Shanika Galaudage , Jacob Golomb , Hui Tong This is my paper · ORCID
classification astro-ph.IMgr-qc
keywords inferencegravitational-wavegwpopulationhierarchicalastronomybayesiancompactdesigned
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. When (not) to trust Monte Carlo approximations for hierarchical Bayesian inference

    astro-ph.HE 2025-09 conditional novelty 7.0 of 10

    A unified error statistic E-hat measures information lost to Monte Carlo noise in hierarchical Bayesian inference, with a recommended cutoff of 0.2 bits.

  2. Establishing Compactness as a Population Observable in Gravitational-Wave Astronomy

    gr-qc 2026-06 unverdicted novelty 6.0 of 10

    Hierarchical analysis of GWTC-3 yields C_eff = 0.5^{+0.3}_{-0.1} consistent with black holes and limits low-compactness exotic binary merger rate to <0.7 Gpc^{-3} yr^{-1}.

  3. Fortifying gravitational-wave population inference with normalizing flows

    astro-ph.HE 2026-06 conditional novelty 6.0 of 10

    Representing each gravitational-wave event's posterior with a normalizing flow lets analysts generate enough cheap posterior samples to keep the Monte-Carlo variance of population inference below threshold for catalog...

  4. Signatures of a subpopulation of hierarchical mergers in the GWTC-4 gravitational-wave dataset

    gr-qc 2026-01 unverdicted novelty 6.0 of 10

    Using a joint effective-spin and precession-spin model on 155 gravitational-wave events, the authors infer that the hierarchical (second-generation) merger fraction rises sharply above ~46 M_sun and peaks again near 1...

  5. The Long Road to Alignment: Measuring Black Hole Spin Orientation with Expanding Gravitational-Wave Datasets

    astro-ph.HE 2025-05 conditional novelty 6.0 of 10

    Simulated gravitational-wave catalogs show spin-tilt peaks at alignment are hard to confirm even with 1500 events, while integrated tilt fractions are robust.

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