Population Properties of Gravitational-wave Neutron Star-Black Hole Mergers

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Zhu, J.-P.; Wu, S.; Qin, Y.; Zhang, B.; Gao, H. et al.: Population Properties of Gravitational-wave Neutron Star-Black Hole Mergers. In: The astrophysical journal : an international review of spectroscopy and astronomical physics : Part 1 928 (2022), Nr. 2, 167. DOI: https://doi.org/10.3847/1538-4357/ac540c

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/12849

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Sum total of downloads: 38




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Over the course of the third observing run of the LIGO-Virgo-KAGRA Collaboration, several gravitational-wave (GW) neutron star-black hole (NSBH) candidates have been announced. By assuming that these candidates are real signals with astrophysical origins, we analyze the population properties of the mass and spin distributions for GW NSBH mergers. We find that the primary BH mass distribution of NSBH systems, whose shape is consistent with that inferred from the GW binary BH (BBH) primaries, can be well described as a power law with an index of α=4.8-2.8+4.5 plus a high-mass Gaussian component peaking at ∼33-9+14M⊙ . The NS mass spectrum could be shaped as a nearly flat distribution between ∼1.0 and 2.1 M ⊙. The constrained NS maximum mass agrees with that inferred from NSs in our Galaxy. If GW190814 and GW200210 are NSBH mergers, the posterior results of the NS maximum mass would be always larger than ∼2.5 M ⊙ and significantly deviate from that inferred in Galactic NSs. The effective inspiral spin and effective precession spin of GW NSBH mergers are measured to potentially have near-zero distributions. The negligible spins for GW NSBH mergers imply that most events in the universe should be plunging events, which support the standard isolated formation channel of NSBH binaries. More NSBH mergers to be discovered in the fourth observing run would help to more precisely model the population properties of cosmological NSBH mergers. © 2022. The Author(s). Published by the American Astronomical Society.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2022
Appears in Collections:An-Institute

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pos. country downloads
total perc.
1 image of flag of Germany Germany 16 42.11%
2 image of flag of United States United States 11 28.95%
3 image of flag of China China 3 7.89%
4 image of flag of Taiwan Taiwan 1 2.63%
5 image of flag of Portugal Portugal 1 2.63%
6 image of flag of New Zealand New Zealand 1 2.63%
7 image of flag of Netherlands Netherlands 1 2.63%
8 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 1 2.63%
9 image of flag of Indonesia Indonesia 1 2.63%
10 image of flag of United Kingdom United Kingdom 1 2.63%
    other countries 1 2.63%

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