The Impact of High-Mass Clusters on the Binary Black Hole Merger Rate over Cosmic Time
Abstract
We present a cosmological calculation of the binary black hole merger rate from dense star clusters, using a Cluster Monte Carlo (CMC) model grid spanning the full observed parameter space of cluster mass, metallicity, and virial radius. For the first time, we incorporate N=107-particle CMC models into this calculation, including a new solar-metallicity model, extending the CMC Cluster Catalog to the most massive clusters observed in the local Universe. Using an analytic cluster formation model which convolves the cluster formation rate with delay-time distributions from our model suite, we find that the local cluster BBH merger rate is dominated by low-mass (M1 ≲ 20 M⊙) mergers originating from recently formed, high-metallicity clusters. While high-mass clusters are the primary sites of hierarchical (second-generation and higher) mergers, their contribution to the overall merger rate is suppressed by the exponential cutoff of the cluster initial mass function. The hierarchical merger rate is therefore highly sensitive to the exact value of the Schechter mass, MS, suggesting that gravitational wave constraints on the hierarchical merger fraction can independently constrain the high-mass end of the cluster initial mass function. Our cluster formation model reproduces the observed present-day GC number density without fine tuning, and we find MS = 107 M⊙ provides the best match to the observed Virgo GC mass distribution. For this value, 27% of local dynamical mergers are hierarchical, compared to 18% for the canonical value of MS = 106.26 M⊙. Our merger weights, which we make publicly available, can be used for direct comparison with LVK distributions and other formation models.
Related
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BibTeX
@misc{mai2026impact,
title = {{The Impact of High-Mass Clusters on the Binary Black Hole Merger Rate over Cosmic Time}},
author = {Aidan Mai and Kyle Kremer and Fulya Kıroğlu},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.20698},
eprint = {2610.20698},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.20698},
}
RIS
TY - UNPB
TI - The Impact of High-Mass Clusters on the Binary Black Hole Merger Rate over Cosmic Time
AU - Aidan Mai
AU - Kyle Kremer
AU - Fulya Kıroğlu
PY - 2026
DA - 2026/10/14
PB - arXiv
DO - 10.48550/arxiv.2610.20698
UR - https://arxiv.org/abs/2610.20698
AB - We present a cosmological calculation of the binary black hole merger rate from dense star clusters, using a Cluster Monte Carlo (CMC) model grid spanning the full observed parameter space of cluster mass, metallicity, and virial radius. For the first time, we incorporate N=10^7-particle CMC models into this calculation, including a new solar-metallicity model, extending the CMC Cluster Catalog to the most massive clusters observed in the local Universe. Using an analytic cluster formation model which convolves the cluster formation rate with delay-time distributions from our model suite, we find that the local cluster BBH merger rate is dominated by low-mass (M_1 ≲ 20 M_⊙) mergers originating from recently formed, high-metallicity clusters. While high-mass clusters are the primary sites of hierarchical (second-generation and higher) mergers, their contribution to the overall merger rate is suppressed by the exponential cutoff of the cluster initial mass function. The hierarchical merger rate is therefore highly sensitive to the exact value of the Schechter mass, M_S, suggesting that gravitational wave constraints on the hierarchical merger fraction can independently constrain the high-mass end of the cluster initial mass function. Our cluster formation model reproduces the observed present-day GC number density without fine tuning, and we find M_S = 10^7 M_⊙ provides the best match to the observed Virgo GC mass distribution. For this value, 27% of local dynamical mergers are hierarchical, compared to 18% for the canonical value of M_S = 10^6.26 M_⊙. Our merger weights, which we make publicly available, can be used for direct comparison with LVK distributions and other formation models.
ER -