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Parameter Estimation for Low-Mass Eccentric Black Hole Binaries

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arxiv 2402.08039 v1 pith:XTORQK76 submitted 2024-02-12 gr-qc astro-ph.IM

classification gr-qcastro-ph.IM
keywords eccentricitybinaryblackgravitationalsignalswaveeccentricestimation
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Recent studies have shown that orbital eccentricity may indicate dynamical assembly as a formation mechanism for binary black holes. Eccentricity leaves a distinct signature in gravitational wave signals and it may be measured if the binary remains eccentric when it enters the LIGO band. Although eccentricity has not yet been confidently detected, the possibility of detecting eccentric binaries is becoming more likely with the improved sensitivity of gravitational wave detectors such as LIGO, Virgo, and KAGRA. It is crucial to assess the accuracy of current search pipelines in recovering eccentricity from gravitational wave signals if it is present. In this study, we investigate the ability of parameter estimation pipeline RIFT to recover eccentricity in the non-spinning and aligned-spin cases for low mass binary black holes. We use TaylorF2Ecc and TEOBResumS to inject sets of synthetic signals and test how well RIFT accurately recovers key binary black hole parameters. Our findings provide valuable insights into the capability of current parameter estimation methods to detect and measure eccentricity in gravitational wave signals.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Assessing the waveform systematics from parameter estimation to population inference with eccentricity

    astro-ph.HE 2026-07 conditional novelty 6.0 of 10

    Eccentric waveform-model differences, small per event, accumulate across the GWTC-4 catalog and alter inferred redshift evolution and effective-spin population distributions.

  2. Narrowing RIFT: Focused simulation-based-inference for interpreting exceptional GW sources

    astro-ph.IM 2025-05 conditional novelty 6.0 of 10

    The upgraded RIFT pipeline, built around an adaptive-volume Monte Carlo integrator, accurately and efficiently handles exceptional compact binaries with precession or eccentricity, as shown by PP tests, timing benchma...

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