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PreprintCC BY 4.0arXiv

Three subpopulations of binary black holes in mass, spin magnitudes and tilts following GWTC-5

Abstract

The mass and spin distributions of merging binary black holes offer clues to their formation pathways, which remain uncertain. In this work, we model the population of binary black holes using generic subpopulations with distinct mass-ratio, spin-magnitude, and spin-tilt distributions, whose relative contributions vary with primary mass. Using the 259 binary black holes in the fifth LIGO-Virgo-KAGRA catalog (GWTC-5), we resolve three subpopulations with low, medium, and high spins. The low-spin population dominates for primary masses near 35 M⊙, contributes roughly half of the binaries for primary masses of 10 M⊙, and favors nearly equal mass ratios overall; its spins are consistent with both black holes having negligible spin, with a log Bayes factor of log10B =6.1+0.2−0.3 in favor of vanishing spins. The medium-spin population accounts for the other half of the population around primary masses of 10 M⊙ and favors spin magnitudes χi ≈ 0.2 for both components, preferentially aligned orientations, and comparable mass ratios. The high-spin population dominates above primary masses of 60 M⊙ and also contributes at lower masses ∼ 20 M⊙; it favors a rapidly spinning primary (χ1 ≈ 0.7), a broad range of secondary spins, widely distributed spin orientations, and a broad mass-ratio distribution. Allowing for a fourth subpopulation yields no distinct additional mass-ratio or spin distribution, as it becomes degenerate with existing features. To resolve highly concentrated features in spin, we control the variance of standard Monte Carlo likelihood estimators using truncated Gaussian mixture models. Taken together, our results add to a growing body of evidence for substructure in the population of LIGO-Virgo-KAGRA black holes, providing further clues to uncover their formation histories.

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BibTeX
@misc{hussain2026three,
  title = {{Three subpopulations of binary black holes in mass, spin magnitudes and tilts following GWTC-5}},
  author = {Asad Hussain and Maximiliano Isi and Aaron Zimmerman},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.32935},
  eprint = {2610.32935},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.32935},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Three subpopulations of binary black holes in mass, spin magnitudes and tilts following GWTC-5
AU  - Asad Hussain
AU  - Maximiliano Isi
AU  - Aaron Zimmerman
PY  - 2026
DA  - 2026/10/23
PB  - arXiv
DO  - 10.48550/arxiv.2610.32935
UR  - https://arxiv.org/abs/2610.32935
AB  - The mass and spin distributions of merging binary black holes offer clues to their formation pathways, which remain uncertain. In this work, we model the population of binary black holes using generic subpopulations with distinct mass-ratio, spin-magnitude, and spin-tilt distributions, whose relative contributions vary with primary mass. Using the 259 binary black holes in the fifth LIGO-Virgo-KAGRA catalog (GWTC-5), we resolve three subpopulations with low, medium, and high spins. The low-spin population dominates for primary masses near 35 M_⊙, contributes roughly half of the binaries for primary masses of 10 M_⊙, and favors nearly equal mass ratios overall; its spins are consistent with both black holes having negligible spin, with a log Bayes factor of log_10B =6.1^+0.2_−0.3 in favor of vanishing spins. The medium-spin population accounts for the other half of the population around primary masses of 10 M_⊙ and favors spin magnitudes χ_i ≈ 0.2 for both components, preferentially aligned orientations, and comparable mass ratios. The high-spin population dominates above primary masses of 60 M_⊙ and also contributes at lower masses ∼ 20 M_⊙; it favors a rapidly spinning primary (χ_1 ≈ 0.7), a broad range of secondary spins, widely distributed spin orientations, and a broad mass-ratio distribution. Allowing for a fourth subpopulation yields no distinct additional mass-ratio or spin distribution, as it becomes degenerate with existing features. To resolve highly concentrated features in spin, we control the variance of standard Monte Carlo likelihood estimators using truncated Gaussian mixture models. Taken together, our results add to a growing body of evidence for substructure in the population of LIGO-Virgo-KAGRA black holes, providing further clues to uncover their formation histories.
ER  -