First joint population inference on binary black hole eccentricity from GWTC-4 bounds the eccentric branching ratio below 5% at 90% confidence, with results consistent with quasi-circular models but highly model-dependent.
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Polynomial models for the (2,2) post-merger waveform amplitudes of eccentric non-spinning binary black holes are constructed from numerical-relativity data as functions of symmetric mass ratio and two merger-time dynamical parameters.
Dual-model analysis of 162 GW sources disfavors eccentricity for most events but finds potential evidence in GW200129, GW231001, and GW231123.
Eccentric BBH signals recovered with quasi-circular precessing models show biases in chirp mass and χ_p; Bayes factors favor eccentric aligned-spin models when both eccentricity and precession are present.
citing papers explorer
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Population Properties of Binary Black Holes with Eccentricity
First joint population inference on binary black hole eccentricity from GWTC-4 bounds the eccentric branching ratio below 5% at 90% confidence, with results consistent with quasi-circular models but highly model-dependent.
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Highly eccentric non-spinning binary black hole mergers: quadrupolar post-merger waveforms
Polynomial models for the (2,2) post-merger waveform amplitudes of eccentric non-spinning binary black holes are constructed from numerical-relativity data as functions of symmetric mass ratio and two merger-time dynamical parameters.
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Assessing the imprint of eccentricity in GW signatures using two independent waveform models
Dual-model analysis of 162 GW sources disfavors eccentricity for most events but finds potential evidence in GW200129, GW231001, and GW231123.
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Biased parameter inference of eccentric, spin-precessing binary black holes
Eccentric BBH signals recovered with quasi-circular precessing models show biases in chirp mass and χ_p; Bayes factors favor eccentric aligned-spin models when both eccentricity and precession are present.