Mass Function of Stellar Black Holes as Revealed by the LIGO–Virgo–KAGRA Observations

Abstract Ninety gravitational-wave events have been detected by the LIGO–Virgo–KAGRA network and are released in the Gravitational-Wave Transient Catalog. Among these events, 83 cases are definitely binary black hole mergers, since the masses of all the objects involved significantly exceed the upper limit of neutron stars. The black holes in these merger events naturally form two interesting samples, a premerger sample that includes all the black holes before the mergers and a postmerger sample that consists of the black holes generated during the merging processes. The former represents black holes that once existed in the Universe, while the latter represents newly born black holes. Here we present a statistical analysis of these two samples. The nonparametric τ statistic method is adopted to correct for the observational selection effect. The Lynden-Bell C − method is further applied to derive the mass distribution and density function of black holes. It is found that the mass distribution can be expressed as a broken power-law function. More interestingly, the power-law index in the high-mass region is comparable for the two samples. The number density of black holes is found to depend on redshift as ρ ( z ) ∝ z −2.06 — z −2.12 based on the two samples. The implications of these findings on the origin of black holes are discussed.

Authors

Institutions

Publication Details

Journal
The Astrophysical Journal
Published
2024-11-29
DOI
https://doi.org/10.3847/1538-4357/ad8b43
Citations
2
Primary Topic
Pulsars and Gravitational Waves Research
Type
article
Field-Weighted Citation Impact
0.66

Funders

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

Mass Function of Stellar Black Holes as Revealed by the LIGO–Virgo–KAGRA Observations

Ze-Cheng Zou, Yong-Feng Huang, Xiao-Fei Dong, Chen Deng et al.
2 citations
The Astrophysical Journal
Pulsars and Gravitational Waves Research
0.66
article

Mass Function of Stellar Black Holes as Revealed by the LIGO–Virgo–KAGRA Observations

Ze-Cheng Zou, Yong-Feng Huang, Xiao-Fei Dong, Chen Deng, Chen-Ran Hu, Zhi-Bin Zhang, Yang Liu, Xiujuan Li
article en
2 citations

Abstract

Abstract Ninety gravitational-wave events have been detected by the LIGO–Virgo–KAGRA network and are released in the Gravitational-Wave Transient Catalog. Among these events, 83 cases are definitely binary black hole mergers, since the masses of all the objects involved significantly exceed the upper limit of neutron stars. The black holes in these merger events naturally form two interesting samples, a premerger sample that includes all the black holes before the mergers and a postmerger sample that consists of the black holes generated during the merging processes. The former represents black holes that once existed in the Universe, while the latter represents newly born black holes. Here we present a statistical analysis of these two samples. The nonparametric τ statistic method is adopted to correct for the observational selection effect. The Lynden-Bell C − method is further applied to derive the mass distribution and density function of black holes. It is found that the mass distribution can be expressed as a broken power-law function. More interestingly, the power-law index in the high-mass region is comparable for the two samples. The number density of black holes is found to depend on redshift as ρ ( z ) ∝ z −2.06 — z −2.12 based on the two samples. The implications of these findings on the origin of black holes are discussed.

The Astrophysical JournalVol. 977(1)
Qufu Normal University (CN), Astronomy and Space (AU), Nanjing University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Shandong Province, National Key Research and Development Program of China
Peace, Justice and strong institutions
Openalex Percentile: Top 27%
Pulsars and Gravitational Waves Research
0.66
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.