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Reanalysis of binary black hole gravitational wave events for orbital eccentricity signatures

  • Maria de Lluc Planas
  • , Antoni Ramos-Buades
  • , Cecilio García-Quirós
  • , H´ector Estell´es
  • , Sascha Husa
  • , Maria Haney

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

We present a reanalysis of 17 gravitational wave events detected with Advanced LIGO and Advanced Virgo in their first three observing runs, using the new IMRPhenomTEHM model—a phenomenological time-domain multipolar waveform model for aligned-spin black hole binaries in elliptical orbits with two eccentric parameters: eccentricity and mean anomaly. We also analyze all events with the underlying quasicircular model IMRPhenomTHM to study the impact of including eccentricity and compare the eccentric and quasicircular binary hypotheses. The high computational efficiency of IMRPhenomTEHM enables us to explore the impact of two different eccentricity priors—uniform and log-uniform—as well as different sampler and data settings. We find evidence for eccentricity in two publicly available LIGOVirgo- KAGRA events, GW200129 and GW200208_22, with Bayes factors favoring the eccentric hypothesis over the quasicircular aligned-spin scenario: log10 BE=QC ∈ ½1.30þ0.15 −0.15; 5.14þ0.15 −0.15and log10 BE=QC ∈½0.49þ0.08 −0.08; 1.14þ0.08 −0.08, respectively. Additionally, the two high-mass events GW190701 and GW190929 exhibit potential eccentric features. For all four events, we conduct further analyses to study the impact of different sampler settings. We also investigate waveform systematics by exploring the support for spin precession using IMRPhenomTPHM and NRSur7dq4, offering new insights into the formation channels of detected binaries. Our results highlight the importance of considering eccentric waveform models in future observing runs, alongside precessing models, as they can help mitigate potential biases in parameter estimation studies. This will be particularly relevant with the expected increase in the diversity of the binary black hole population with new detectors.
Original languageEnglish
Article number123004
Pages (from-to)1-20
JournalPhysical Review D
Volume112
Issue number12
DOIs
Publication statusPublished - 1 Dec 2025
Externally publishedYes

Funding

The authors would like to thank Nihar Gupte for the LSC Publication and Presentation Committee review of this manuscript. We thankfully acknowledge the computer resources (MN5 Supercomputer), technical expertise, and assistance provided by Barcelona Supercomputing Center (BSC) through funding from the Red Española de Supercomputación (RES) (AECT-2024-3-0027); and the computer resources (Picasso Supercomputer), technical expertise, and assistance provided by the SCBI (Supercomputing and Bioinformatics) center of the University of Málaga (AECT-2025-1-0035). This research has made use of data or software obtained from the Gravitational Wave Open Science Center, a service of the LIGO Scientific Collaboration, the Virgo Collaboration, and KAGRA. This material is based upon work supported by NSF’s LIGO Laboratory which is a major facility fully funded by the National Science Foundation. LIGO is funded by the U.S. National Science Foundation. Virgo is funded by the French Centre National de Recherche Scientifique (CNRS), the Italian Istituto Nazionale della Fisica Nucleare (INFN), and the Dutch Nikhef, with contributions by Polish and Hungarian institutes. M. d. L. P. is supported by the Spanish Ministry of Universities via an FPU Doctoral Grant (No. FPU20/05577, EST24/00621). A. R.-B. is supported by the Veni research program which is (partly) financed by the Dutch Research Council (NWO) under the Grant No. VI.Veni.222.396, acknowledges support from the Spanish Agencia Estatal de Investigación Grants No. PID2024-157460NA-I00 and No. PID2022-138626NB-I00 funded by MICIU/AEI/ 10.13039/ 501100011033 and the ERDF/EU, and is supported by the Spanish Ministerio de Ciencia, Innovación y Universidades (Beatriz Galindo, BG23/00056) and cofinanced by UIB. C. G. is supported by the Swiss National Science Foundation (SNSF) Ambizione Grant No. PZ00P2_223711. This work was supported by the Universitat de les Illes Balears (UIB); the Spanish Agencia Estatal de Investigación Grants No. PID2022-138626NB-I00, No. PID2019-106416GB-I00, No. RED2022-134204-E, No. RED2022-134411-T, funded by MCIN/AEI/10.13039/501100011033; the MCIN with funding from the European Union NextGenerationEU/PRTR (PRTR-C17.I1); Comunitat Autonòma de les Illes Balears through the Direcció General de Recerca, Innovació I Transformació Digital with funds from the Tourist Stay Tax Law (PDR2020/11-ITS2017-006), the Conselleria d’Economia, Hisenda i Innovació Grants No. SINCO2022/18146 and No. SINCO2022/6719, cofinanced by the European Union and FEDER Operational Program 2021-2027 of the Balearic Islands; and the “ERDF A way of making Europe.”

FundersFunder number
Comunitat Autonòma de les Illes Balears
Direcció General de Recerca
National Science Foundation
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Direcció General de Recerca, Generalitat de Catalunya
KAGRA
Centre National de la Recherche Scientifique
European Commission
Barcelona Supercomputing Center
Istituto Nazionale di Fisica Nucleare
Ministerio de UniversidadesFPU20/05577, EST24/00621
Agencia Estatal de InvestigaciónPID2024-157460NA-I00, PID2022-138626NB-I00
Universitat de les Illes BalearsRED2022-134411-T, RED2022-134204-E, PID2019-106416GB-I00
Tourist Stay Tax LawPDR2020/11-ITS2017-006
Ministerio de Ciencia, Innovación y UniversidadesBG23/00056
PRTRPRTR-C17
Conselleria d’EconomiaSINCO2022/18146, SINCO2022/6719
European Regional Development Fund2021-2027
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungPZ00P2_223711
Universidad de MálagaAECT-2025-1-0035
Red Española de SupercomputaciónAECT-2024-3-0027

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