A Rosetta Stone for eccentric gravitational waveform models
Alan M. Knee, Isobel M. Romero-Shaw, Paul D. Lasky, Jess McIver, Eric, Thrane

TL;DR
This paper develops a framework to translate between different definitions of orbital eccentricity in gravitational waveform models, enabling consistent comparisons and interpretations of eccentricity measurements in binary black hole mergers.
Contribution
The authors introduce a systematic method to map eccentricity parameters between two waveform models, aiding in consistent eccentricity estimation across models and simulations.
Findings
A 20-50% smaller eccentricity input in TEOBResumS matches the same eccentricity in SEOBNRE.
The mapping is validated using numerical relativity simulations.
Framework improves comparison of eccentricity measurements across models.
Abstract
Orbital eccentricity is a key signature of dynamical binary black hole formation. The gravitational waves from a coalescing binary contain information about its orbital eccentricity, which may be measured if the binary retains sufficient eccentricity near merger. Dedicated waveforms are required to measure eccentricity. Several models have been put forward, and show good agreement with numerical relativity at the level of a few percent or better. However, there are multiple ways to define eccentricity for inspiralling systems, and different models internally use different definitions of eccentricity, making it difficult to directly compare eccentricity measurements. In this work, we systematically compare two eccentric waveform models, and , by developing a framework to translate between different definitions of eccentricity. This mapping is…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsPulsars and Gravitational Waves Research · Astrophysical Phenomena and Observations · Geophysics and Sensor Technology
