Wolf–Rayet–compact object binaries as progenitors of binary compact objects

Binaries with a Wolf–Rayet star and a compact object (WR–COs), either a black hole (BH) or a neutron star (NS), have been proposed as possible progenitors for the binary compact object mergers (BCOs) observed with gravitational wave (GW) detectors. In this work, we use the open source population synthesis code SEVN to investigate the role of WR–COs as BCO progenitors. We consider an initial population of 5 × 10 6 binaries, and we evolve it across 96 combinations of metallicities, common envelope efficiencies, core-collapse supernova models, and natal kick distributions. We find that WR–COs are the progenitors of most BCOs, especially at high and intermediate metallicity. At Z = 0.02, 0.014, and 0.0014, more than ≳ 99% of all the BCOs in our simulations evolved as WR–COs. At Z = 0.00014, inefficient binary stripping lowers the fraction of BCOs with WR–CO progenitors to ≈83–95%. Despite their key role in BCO production, only ≈5–30% of WR–COs end their life as BCOs. We find that Cyg X-3, the only WR–CO candidate observed in the Milky Way, is a promising BCO progenitor, especially if it hosts a BH. In our simulations, about 70–100% of the Cyg X-3-like systems in the WR–BH configuration (BH mass ≤ 10 M ⊙ ) are BCO progenitors, in agreement with the literature. Future observations of WR–COs similar to Cyg X-3 may be the Rosetta stone to interpret the formation of BCOs.

Authors

Institutions

Publication Details

Journal
Astronomy and Astrophysics
Published
2025-02-20
DOI
https://doi.org/10.1051/0004-6361/202452585
Citations
2
Primary Topic
Astro and Planetary Science
Type
article
Field-Weighted Citation Impact
2.31

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Wolf–Rayet–compact object binaries as progenitors of binary compact objects

Erika Korb, Guglielmo Costa, Michela Mapelli, Giuliano Iorio et al.
2 citations
Astronomy and Astrophysics
Astro and Planetary Science
2.31
article

Wolf–Rayet–compact object binaries as progenitors of binary compact objects

Erika Korb, Guglielmo Costa, Michela Mapelli, Giuliano Iorio, Marco Dall’Amico
article en
2 citations

Abstract

Binaries with a Wolf–Rayet star and a compact object (WR–COs), either a black hole (BH) or a neutron star (NS), have been proposed as possible progenitors for the binary compact object mergers (BCOs) observed with gravitational wave (GW) detectors. In this work, we use the open source population synthesis code SEVN to investigate the role of WR–COs as BCO progenitors. We consider an initial population of 5 × 10 6 binaries, and we evolve it across 96 combinations of metallicities, common envelope efficiencies, core-collapse supernova models, and natal kick distributions. We find that WR–COs are the progenitors of most BCOs, especially at high and intermediate metallicity. At Z = 0.02, 0.014, and 0.0014, more than ≳ 99% of all the BCOs in our simulations evolved as WR–COs. At Z = 0.00014, inefficient binary stripping lowers the fraction of BCOs with WR–CO progenitors to ≈83–95%. Despite their key role in BCO production, only ≈5–30% of WR–COs end their life as BCOs. We find that Cyg X-3, the only WR–CO candidate observed in the Milky Way, is a promising BCO progenitor, especially if it hosts a BH. In our simulations, about 70–100% of the Cyg X-3-like systems in the WR–BH configuration (BH mass ≤ 10 M ⊙ ) are BCO progenitors, in agreement with the literature. Future observations of WR–COs similar to Cyg X-3 may be the Rosetta stone to interpret the formation of BCOs.

Astronomy and AstrophysicsVol. 695
Université Claude Bernard Lyon 1 (FR), École Normale Supérieure de Lyon (FR), Centre National de la Recherche Scientifique (FR), Heidelberg University (DE), Centre de Recherche Astrophysique de Lyon (FR), Istituto Nazionale di Fisica Nucleare, Sezione di Padova (IT), Osservatorio Astronomico di Padova (IT)
European Commission, Deutsche Forschungsgemeinschaft, Agence Nationale de la Recherche, European Research Council
Openalex Percentile: Top 13%
Astro and Planetary Science
2.31
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.