Abstract
The third Gravitational-wave Transient Catalog (GWTC-3) describes signals detected with Advanced LIGO and Advanced Virgo up to the end of their third observing run. Updating the previous GWTC-2.1, we present candidate gravitational waves from compact binary coalescences during the second half of the third observing run (O3b) between 1 November 2019, 15:00 UTC and 27 March 2020, 17:00 UTC. There are 35 compact binary coalescence candidates identified by at least one of our search algorithms with a probability of astrophysical origin pastro>0.5. Of these, 18 were previously reported as low-latency public alerts, and 17 are reported here for the first time. Based upon estimates for the component masses, our O3b candidates with pastro>0.5 are consistent with gravitational-wave signals from binary black holes or neutron star-black hole binaries, and we identify none from binary neutron stars. However, from the gravitational-wave data alone, we are not able to measure matter effects that distinguish whether the binary components are neutron stars or black holes. The range of inferred component masses is similar to that found with previous catalogs, but the O3b candidates include the first confident observations of neutron star-black hole binaries. Including the 35 candidates from O3b in addition to those from GWTC-2.1, GWTC-3 contains 90 candidates found by our analysis with pastro>0.5 across the first three observing runs. These observations of compact binary coalescences present an unprecedented view of the properties of black holes and neutron stars.
| Original language | English |
|---|---|
| Article number | 041039 |
| Number of pages | 89 |
| Journal | Physical Review X |
| Volume | 13 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 4 Dec 2023 |
Bibliographical note
Acknowledgments:Calibration of the LIGO strain data was performed with gstlal-based calibration software pipeline [45]. Calibration of the Virgo strain data is performed with c-based software [53]. Data-quality products and event-validation results were computed using the dmt [417], dqr [76], dqsegdb [418], gwdetchar [419], hveto [420], idq [421], omicron [65] and pythonvirgotools [422] software packages and contributing software tools. Analyses in this catalog relied upon the lalsuite software library [423]. The detection of the signals and subsequent significance evaluations in this catalog were performed with the gstlal-based inspiral software pipeline [78–81], with the mbta pipeline [82,83], and with the pycbc [86–88] and the cwb [60,89,90] packages. Estimates of the noise spectra and glitch models were obtained using bayeswave [377,379,383]. Noise subtraction for one candidate was also performed with gwsubtract [44]. Source-parameter estimation was performed with the bilby and parallel bilby libraries [144–146] using the dynesty nested sampling package [424], and the rift library [147–149], with the lalinference [376] libraries used for initial analyses. pesummary was used to postprocess and collate parameter-estimation results [425]. The various stages of the parameter-estimation analysis were managed with the asimov library [426]. Plots were prepared with matplotlib [427], seaborn [428] and gwpy [429]. numpy [430] and scipy [431] were used in the preparation of the manuscript. This material is based upon work supported by NSF’s LIGO Laboratory which is a major facility fully funded by the National Science Foundation. The authors also gratefully acknowledge the support of the Science and Technology Facilities Council (STFC) of the United Kingdom, the Max-Planck-Society, and the State of Niedersachsen/Germany for support of the construction of Advanced LIGO and construction and operation of the GEO 600 detector. Additional support for Advanced LIGO was provided by the Australian Research Council. The authors gratefully acknowledge the Italian Istituto Nazionale di Fisica Nucleare (INFN), the French Centre National de la Recherche Scientifique (CNRS), and the Netherlands Organization for Scientific Research, for the construction and operation of the Virgo detector and the creation and support of the EGO consortium. The authors also gratefully acknowledge research support from these agencies as well as by the Council of Scientific and Industrial Research of India, the Department of Science and Technology, India, the Science & Engineering Research Board, India, the Ministry of Human Resource Development, India, the Spanish Agencia Estatal de Investigación, the Vicepresidència i Conselleria d’Innovació, Recerca i Turisme, and the Conselleria d’Educació i Universitat del Govern de les Illes Balears, the Conselleria d’Innovació, Universitats, Ciència i Societat Digital de la Generalitat Valenciana, and the CERCA Programme Generalitat de Catalunya, Spain, the National Science Centre of Poland and the Foundation for Polish Science, the Swiss National Science Foundation, the Russian Foundation for Basic Research, the Russian Science Foundation, the European Commission, the European Regional Development Funds, the Royal Society, the Scottish Funding Council, the Scottish Universities Physics Alliance, the Hungarian Scientific Research Fund, the French Lyon Institute of Origins, the Belgian Fonds de la Recherche Scientifique, Actions de Recherche Concertées and Fonds Wetenschappelijk Onderzoek—Vlaanderen, Belgium, the Paris Île-de-France Region, the National Research, Development and Innovation Office Hungary, the National Research Foundation of Korea, the Natural Science and Engineering Research Council Canada, Canadian Foundation for Innovation, the Brazilian Ministry of Science, Technology, and Innovations, the International Center for Theoretical Physics South American Institute for Fundamental Research, the Research Grants Council of Hong Kong, the National Natural Science Foundation of China, the Leverhulme Trust, the Research Corporation, the Ministry of Science and Technology, Taiwan, the United States Department of Energy, and the Kavli Foundation. The authors gratefully acknowledge the support of the NSF, STFC, INFN, and CNRS for provision of computational resources. Computing was performed on the OzSTAR Australian national facility at Swinburne University of Technology, which receives funding in part from the Astronomy National Collaborative Research Infrastructure Strategy allocation provided by the Australian Government. We thankfully acknowledge the computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center (Grant No. RES-AECT-2021-2-0021). This work was supported by MEXT, JSPS Leading-edge Research Infrastructure Program, JSPS Grant-in-Aid for Specially Promoted Research, Grant No. 26000005, JSPS Grant-in-Aid for Scientific Research on Innovative Areas 2905: Grants No, JP17H06358, No. JP17H06361, and No. JP17H06364, JSPS Core-to-Core Program A. Advanced Research Networks, JSPS Grant-in-Aid for Scientific Research (S) Grant No. 17H06133, the joint research program of the Institute for Cosmic Ray Research, University of Tokyo, National Research Foundation and Computing Infrastructure Project of KISTI-GSDC in Korea, Academia Sinica, AS Grid Center and the Ministry of Science and Technology in Taiwan under grants including Grant No. AS-CDA-105-M06, Advanced Technology Center of NAOJ, and Mechanical Engineering Center of KEK. We thank the anonymous journal referees for helpful comments.