A mixture-model framework for combining gravitational-wave tests of General Relativity yields Bayes factors of 10-20 favoring GR, substantially lower than existing methods that assume uniform deviations across events.
No evidence that the majority of black holes in binaries have zero spin
5 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
abstract
The spin properties of merging black holes observed with gravitational waves can offer novel information about the origin of these systems. The magnitude and orientations of black hole spins offer a record of binaries' evolutionary history, encoding information about massive stellar evolution and the astrophysical environments in which binary black holes are assembled. Recent analyses of the binary black hole population have yielded conflicting portraits of the black hole spin distribution. Some work suggests that black hole spins are small but non-zero and exhibit a wide range of misalignment angles relative to binaries' orbital angular momenta. Other work concludes that the majority of black holes are non-spinning while the remainder are rapidly rotating and primarily aligned with their orbits. We revisit these conflicting conclusions, employing a variety of complementary methods to measure the distribution of spin magnitudes and orientations among binary black hole mergers. We find that the existence of a sub-population of black hole with vanishing spins is not required by current data. Should such a sub-population exist, we conclude that it must contain $\lesssim 60\%$ of binaries. Additionally, we find evidence for significant spin-orbit misalignment among the binary black hole population, with some systems exhibiting misalignment angles greater than $90^{\circ}$, and see no evidence for an approximately spin-aligned sub-population.
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Dynamical formation in globular clusters produces a robust second black-hole mass peak at ~70 solar masses from second-generation mergers when the first-generation spectrum is truncated by pair-instability supernovae.
Maximum-likelihood-based posterior predictive checks detect model misspecification better than event-level versions for uncertain spin tilts, but current detector sensitivity limits their power; the Gaussian Component Spins model underpredicts high spin magnitudes and overpredicts anti-aligned tilts
Neural spline flows perform fast posterior inference on 11-dimensional millilensed GW parameters with accuracy comparable to dynesty for most quantities and a 3-day to 0.8-second speedup.
Spin sorting with the default spin model distinguishes spinning and nonspinning binary black hole populations in simulations and shows real data rule out a fully nonspinning population but allow mixed ones with up to 80% nonspinning sources.
citing papers explorer
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Testing General Relativity with GWTC-4.0 through mixture models
A mixture-model framework for combining gravitational-wave tests of General Relativity yields Bayes factors of 10-20 favoring GR, substantially lower than existing methods that assume uniform deviations across events.
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Second-Generation Mass Peak in the Gravitational-Wave Population as a Probe of Globular Clusters
Dynamical formation in globular clusters produces a robust second black-hole mass peak at ~70 solar masses from second-generation mergers when the first-generation spectrum is truncated by pair-instability supernovae.
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Posterior Predictive Checks for Gravitational-wave Populations: Limitations and Improvements
Maximum-likelihood-based posterior predictive checks detect model misspecification better than event-level versions for uncertain spin tilts, but current detector sensitivity limits their power; the Gaussian Component Spins model underpredicts high spin magnitudes and overpredicts anti-aligned tilts
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Parameter inference of millilensed gravitational waves using neural spline flows
Neural spline flows perform fast posterior inference on 11-dimensional millilensed GW parameters with accuracy comparable to dynesty for most quantities and a 3-day to 0.8-second speedup.
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Disentangling spinning and nonspinning binary black hole populations with spin sorting
Spin sorting with the default spin model distinguishes spinning and nonspinning binary black hole populations in simulations and shows real data rule out a fully nonspinning population but allow mixed ones with up to 80% nonspinning sources.