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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4 Pith papers cite this work. Polarity classification is still indexing.
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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.
Deep learning models on simulated ET and CE data achieve higher accuracy (0.655–0.897) than matched filtering (0.514–0.689) at classifying g-mode resonances versus adiabatic tides, point particles, and noise in eccentric binary neutron star signals.
GWTC-3 catalogs 90 compact binary coalescence events with p_astro > 0.5 from LIGO and Virgo's first three observing runs, including the first confident neutron star-black hole binaries.
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GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run
GWTC-3 catalogs 90 compact binary coalescence events with p_astro > 0.5 from LIGO and Virgo's first three observing runs, including the first confident neutron star-black hole binaries.