A reference-frequency-independent detection statistic for eccentric binary mergers is introduced and applied to GW200105, yielding ln B ≤ 0.9 in favor of the eccentric aligned-spin model over the quasi-circular precessing model.
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No GWTC-3 event robustly prefers a non-BBH merger morphology once low-frequency cutoffs are raised; apparent low-compactness modes are noise artifacts, with GW231123 left as an unresolved special case.
SEOBNRv6EHM reduces parameter biases for eccentric binaries versus prior models and shows mild support for eccentricity in five catalog events plus comparable unbound fits for three high-mass events.
Neural network surrogate approximates precessing compact binary gravitational waveforms up to 1000x faster than the base EOB model with validated accuracy.
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 15.7 M_sun.
Bayesian inference on LVK O1-O3 events with eccentric aligned-spin waveforms yields log10 Bayes factors of 1.77-4.75 favoring eccentricity for GW200129, GW190701 and GW200208_22, and >99.5% probability that at least one of 57 events is eccentric under an astrophysically motivated rate prior.
Neural post-Einsteinian analysis of GWTC-3 finds no GR violation and sets constraints covering both post-Newtonian and beyond-post-Newtonian deviations in a single theory-agnostic setup.
DQRbuild toolkit automates data quality vetting for gravitational-wave events, recovering 96% of human-identified issues from O3 with a 24% false alarm rate.
Reanalysis of flagged LVK events with waveform uncertainty models produces consistent spin and precession inferences across raw/deglitched data and multiple waveform approximants.
citing papers explorer
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A universal framework to identify eccentric binary mergers: GW200105 case study
A reference-frequency-independent detection statistic for eccentric binary mergers is introduced and applied to GW200105, yielding ln B ≤ 0.9 in favor of the eccentric aligned-spin model over the quasi-circular precessing model.
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Compactness Inference in Gravitational-Wave Mergers with PhenomDECO: Catalog Benchmarks and Robustness Diagnostics
No GWTC-3 event robustly prefers a non-BBH merger morphology once low-frequency cutoffs are raised; apparent low-compactness modes are noise artifacts, with GW231123 left as an unresolved special case.
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Eccentric and unbound compact binaries in the LIGO-Virgo-KAGRA catalog: parameter estimation and waveform systematics with SEOBNRv6EHM
SEOBNRv6EHM reduces parameter biases for eccentric binaries versus prior models and shows mild support for eccentricity in five catalog events plus comparable unbound fits for three high-mass events.
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Fast neural network surrogate for multimodal effective-one-body gravitational waveforms from generically precessing compact binaries
Neural network surrogate approximates precessing compact binary gravitational waveforms up to 1000x faster than the base EOB model with validated accuracy.
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Signatures of a subpopulation of hierarchical mergers in the GWTC-4 gravitational-wave dataset
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 15.7 M_sun.
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Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA
Bayesian inference on LVK O1-O3 events with eccentric aligned-spin waveforms yields log10 Bayes factors of 1.77-4.75 favoring eccentricity for GW200129, GW190701 and GW200208_22, and >99.5% probability that at least one of 57 events is eccentric under an astrophysically motivated rate prior.
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Neural Post-Einsteinian Test of General Relativity with the Third Gravitational-Wave Transient Catalog
Neural post-Einsteinian analysis of GWTC-3 finds no GR violation and sets constraints covering both post-Newtonian and beyond-post-Newtonian deviations in a single theory-agnostic setup.
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Rapid data quality investigations of gravitational-wave events with the Data Quality Report Builder toolkit
DQRbuild toolkit automates data quality vetting for gravitational-wave events, recovering 96% of human-identified issues from O3 with a 24% false alarm rate.
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Mitigating Systematic Errors in Parameter Estimation of Binary Black Hole Mergers in O1-O3 LIGO-Virgo Data
Reanalysis of flagged LVK events with waveform uncertainty models produces consistent spin and precession inferences across raw/deglitched data and multiple waveform approximants.