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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Neural network surrogate approximates precessing compact binary gravitational waveforms up to 1000x faster than the base EOB model with validated accuracy.
GWTC-4 data show a transition to nearly all hierarchical mergers above 46 solar masses, with the hierarchical rate peaking at 15.7 solar masses, indicating mass-dependent substructure in black hole spins.
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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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
GWTC-4 data show a transition to nearly all hierarchical mergers above 46 solar masses, with the hierarchical rate peaking at 15.7 solar masses, indicating mass-dependent substructure in black hole spins.
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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.