ACORN I. Massive Black Hole Seeding and Tidal Disruption Events from Star Clusters in Cosmological Simulations

arXiv:2610.12398 · astro-ph.GA, astro-ph.HE · Submitted 2026-10-08 · Read on arXiv

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Introduction to the show: ident: Astrophysics Radio. Generated commentary on the latest astrophysics papers.

Vera: I'm Vera, and with me are Jocelyn and Subrahmanyan, guest researcher.

Jocelyn: Today's paper: "ACORN I. Massive Black Hole Seeding and Tidal Disruption Events from Star Clusters in Cosmological Simulations".

Vera: The gist The authors introduce a new MBH seeding model for cosmological simulations, physically motivated by runaway collisions in star clusters, to explain massive black holes observed at high redshift.

Jocelyn: First, who's behind it and why it matters.

Title and authors: Jocelyn: Okay, so what's the actual setup of this model they’re describing in ACORN I? It seems pretty detailed about how they are modeling the star cluster population itself before even looking at the black hole seeds.

Vera: Well, they start by identifying regions that host these star clusters using something called StarFOF, which is a Friends-of-Friends algorithm where star particles link everything together <ref:2610.12398#pg1>. Then they calculate the total mass budget for those clusters in that region.

Subrahmanyan: And they apply a power-law initial cluster mass function with a slope of-two within the range of one hundred two to one hundred eight Msun, which sets up the initial population structure for their simulations.

Jocelyn: After setting up the clusters, they use an analytic framework developed by Williams et al. 2026b to predict the mass of those black hole seeds based on the properties of their host clusters <ref:2610.12398#pg3>.

Vera: And this model imposes a minimum seed mass constraint, setting Mseed,min at one hundred three h-1Msun in this work, which basically filters out the smaller seeds they don't want to focus on right now.

Subrahmanyan: The summary highlights that they are exploring alternative pathways too, like successive black hole mergers within sufficiently massive and compact nuclear clusters leading to a seed <ref:2610.12398#pg3>.

Jocelyn: And then they bring in the tidal disruption events, or TDEs, which are crucial because they show how these seeds actually interact with the evolving clusters over time.

The paper's summary: Vera: Now for the improvements they propose to this model, and honestly, I think those are really where the real traction is. They suggest using TDEs not just as a passive outcome but as an active channel for feeding young black holes <ref:2610.12398#pg3>.

Subrahmanyan: They also mention that if you look at MBH binary systems, like those with eccentric Kozai-Lidov mechanisms, the TDE rate can be enhanced significantly <ref:2610.12398#pg3>.

Jocelyn: That enhancement is tied to the gravitational wave recoil velocity calculation, which depends on the mass ratio q of the progenitor black holes <ref:2610.12398#pg4>. If that recoil speed exceeds the escape velocity of the cluster, they label that cluster mass as zero, meaning a very energetic ejection event happens.

Vera: So another improvement is linking it back to galaxy properties—the paper claims this gives a more physical MBH-galaxy scaling relation for low-mass galaxies, specifically those with Mgalaxy around ten six to nine Msun <ref:2610.12398#pg5>.

Subrahmanyan: That scaling is particularly valuable because previous models struggled to describe that regime of low-mass galaxies accurately; this approach ties the seed mass directly to the local environment, which is a big step forward for galaxy modeling.

Jocelyn: They also show how they can control the comparison between different seeding models by running constrained simulations in an overdense region, instead of just making a statistical prediction for all of cosmology <ref:2610.12398#pg5>.

The paper's improvements: Vera: So, wrapping up ACORN I Massive Black Hole Seeding and Tidal Disruption Events from Star Clusters in Cosmological Simulations, the paper shows that this star-cluster-based seeding model produces a strong link between black holes and their host environments.

Jocelyn: It connects the abundance of black holes to where they form—meaning more seeds are produced within the same dark matter halo because multiple black holes can form in situ <ref:2610.12398#pg5>.

Subrahmanyan: The paper also shows that the central black hole masses increase systematically with galaxy masses, and that the seed mass distribution follows a power-law with a slope of-one similar to what we see in other simulations like AMBRA and ASTRID <ref:2610.12398#pg5>.

Vera: It confirms that massive seeds form preferentially in those massive, compact, and metal-poor star clusters we identified earlier.

Jocelyn: And they show how the occupation fraction of these black holes gradually increases with both total halo mass and halo stellar mass <ref:2610.12398#pg5>.

Subrahmanyan: It’s a solid framework for understanding how galaxy growth relates to the seeds we start with, which is crucial for connecting early universe physics to what we observe today.

Vera: So, this work on ACORN I Massive Black Hole Seeding and Tidal Disruption Events from Star Clusters in Cosmological Simulations really gives us a physical connection between the stars in a cluster and the massive black holes that live around them.

Jocelyn: It opens up new ways to test these models by allowing for controlled comparisons in extreme overdense regions, and it offers better predictions for low-mass galaxies <ref:2610.12398#pg5>.

Subrahmanyan: It’s a step toward a more self-consistent picture where the black hole seed mass is determined self-consistently from its host star cluster properties, which is what we need to move forward in this field.

Conclusion: Vera: So we’ve been looking at ACORN I Massive Black Hole Seeding and Tidal Disruption Events from Star Clusters in Cosmological Simulations, and what this study really nails is how the formation of those massive black hole seeds is tied directly to the local environment.

Jocelyn: Exactly. They show that by modeling the star clusters—how they evolve through stellar deaths and collisions—you get a much more physical picture than just picking a random seed mass <ref:2610.12398#pg5>.

Subrahmanyan: And the implication for me is that we're finally getting a way to connect the very small-scale star cluster physics, like metallicity and stellar winds, to the massive black holes we see at high redshift.

Vera: Right. They set a minimum seed mass of one hundred three h-1Msun, which filters out the really tiny ones, but they also show that because multiple black holes can form in one halo <ref:2610.12398#pg5>, you get a much more abundant population than if you only looked at gas or halo models.

Jocelyn: And the part about TDEs is interesting because it shows how these seeds actually start feeding, especially when they are in binary systems, which can be boosted by things like the Kozai-Lidov mechanism <ref:2610.12398#pg3>.

Subrahmanyan: That goes back to the core idea of this paper, linking the environment—the cluster mass and metallicity—to both how many seeds you get and what mass those seeds end up having.

Vera: The scaling relation for low-mass galaxies is what really stands out here because it addresses a regime that previous seeding models just couldn't handle well <ref:2610.12398#pg5>.

Jocelyn: It’s like they’re giving us a better yardstick to predict how black holes grow in those smaller systems we observe out there.

Subrahmanyan: And looking ahead, the constrained simulation approach is useful because it lets us test these different physical rules directly, not just make a statistical guess about the whole universe <ref:2610.12398#pg5>.

Vera: It’s a solid piece of work on ACORN I Massive Black Hole Seeding and Tidal Disruption Events from Star Clusters in Cosmological Simulations.

Jocelyn: It really shows that the seeds we start with matter way more than we thought when we look at them through the lens of star cluster evolution.

Subrahmanyan: This makes me think about how this same idea might apply to other processes, like those gravitational wave recoils we’ve been looking into recently.

Yihao Zhou, Tiziana Di Matteo, Claire E. Williams, Aklant Kumar Bhowmick, Marta Reina-Campos, Carl L. Rodriguez, Elena Gonzalez Prieto , Laura Blecha

McWilliams Center for Cosmology, Department of Physics, Carnegie Mellon University · Department of Physics and Astronomy, UCLA · Mani L. Bhaumik Institute for Theoretical Physics, Department of Physics and Astronomy, UCLA · University of Virginia 530 McCormick Rd Charlottesville · Virginia Institute for Theoretical Astronomy, University of Virginia · The NSF-Simons AI Institute for Cosmic Origins

astro-ph.GA, astro-ph.HE

Submitted: 2026-10-08

Updated: 2026-10-08

Comments: 32 pages, 24 figures. Comments are welcome!

License: http://creativecommons.org/licenses/by/4.0/

Importance score: 69/100

The gist: The gist The authors introduce a new MBH seeding model for cosmological simulations, physically motivated by runaway collisions in star clusters, to explain massive black holes observed at high

Key concepts

Star-Cluster-Based MBH Seeding Model: This model generates MBH seeds by simulating the evolution of subgrid star clusters, which form from the local interstellar medium. The mass of these seeds is determined by how massive and metal-rich their host clusters are, linking seed properties directly to the local environment.
Tidal Disruption Events (TDEs): TDEs occur when a black hole interacts with a star cluster, causing it to be torn apart. The model tracks these events, noting that they can be boosted if the MBH is in a binary system, and they are crucial for growing lower-mass seeds.
Runaway Collisions in Star Clusters: This physical process describes how stars within a dense star cluster collide violently, leading to runaway mergers. The energy and mass of these collisions dictate the final mass of the MBH seed formed from this process, making it a core mechanism for seed formation.

Terminology

Metallicity — 26× in this paper · explained in 3 episodes
Trace — 11× in this paper · explained in 2 episodes
Abundance — 8× in this paper · explained in 1 episode
Velocity Dispersion — 5× in this paper · explained in 2 episodes
AGN — 3× in this paper
AGN Feedback — 3× in this paper
Core — 2× in this paper · explained in 2 episodes
Initial Mass Function (IMF) — 2× in this paper · explained in 2 episodes
N-body simulations — 2× in this paper · explained in 2 episodes
Cluster expansion — 1× in this paper · explained in 2 episodes
Clustering — 1× in this paper · explained in 2 episodes
Consistency — 1× in this paper · explained in 3 episodes
Gravitational Lensing — 1× in this paper · explained in 2 episodes
James Webb Space Telescope — 1× in this paper
Little Red Dots — 1× in this paper · explained in 2 episodes
Little Red Dots (LRDs) — 1× in this paper · explained in 4 episodes
Stellar Feedback — 1× in this paper · explained in 2 episodes

Summary

The gist The authors introduce a new MBH seeding model for cosmological simulations, physically motivated by runaway collisions in star clusters, to explain massive black holes observed at high redshift.

How it works

The model generates subgrid star clusters according to the local ISM and evolves them through stellar evolution and two-body relaxation.
The masses of MBH seeds formed through runaway collisions are determined by the properties of their host clusters, including the effects of metallicity-dependent stellar winds.
Tidal disruption events (TDEs) are followed with the evolving clusters, which can be enhanced in MBH binaries, and gravitational-wave (GW) recoil following MBH mergers are accounted for.
The model is implemented in a constrained simulation of a 5σ overdense region, where seeds of 103 −105.6 M⊙ form in clusters with 104 ≤ mSC ≤ 108 M⊙.
Because both the seed abundance and mass are directly connected to the local environment, it provides a more physical MBH−Mgalaxy scaling for low-mass galaxies (Mgalaxy ∼ 106−9 M⊙), a regime poorly described by previous seeding models.

Star-Cluster-Based MBH Seeding Model

The model involves several steps: identify the stellar structures that host the star cluster populations, estimate the mass budget for the star clusters, generate the star cluster population, estimate the MBH seed mass within each star cluster, and seed the MBH particle in simulations.

StarFOF is used to identify regions that host a star cluster population using a Friends-of-Friends (FoF) algorithm with star particles as primary linking particles.
The total cluster mass budget in a StarFOF is computed as MSC,sFOF = P i Γ i m⋆,i, where the sum is over the member star particles.
Cluster masses follow a power-law initial cluster mass function (ICMF) with a slope of −2 within the mass range 102 − 108 M⊙.
The MBH seed mass is predicted using an analytic model developed by Williams et al. (2026b), which predicts the VMS mass based on the properties of their host clusters.
A minimum MBH seed mass of Mseed,min = 103 h−1M⊙ is imposed in this work.

Star Cluster Evolution and Interactions

The star clusters experience mass loss due to stellar evolution, two-body relaxation, and TDEs.

Mass loss from stellar evolution is inherited from the mass return model in ASTRID, assuming a Chabrier initial mass function (IMF).
The dynamical evolution of the cluster size is given by drh/rh = 2 − ζ ξ dmrlx/mSC.
TDEs contribute to mass loss and accretion, with the rate determined by evolved star cluster properties, which can be boosted within binary systems.

TDEs and Gravitational Wave Recoil

TDEs provide a channel for feeding young MBHs, with the isolated TDE rate given by an empirical formula.

In MBH binary systems, the TDE rate can be enhanced by the eccentric Kozai-Lidov (EKL) mechanism.
The GW recoil velocity is calculated using a formula dependent on the mass ratio q of the progenitor MBHs.
If the recoil velocity exceeds the escape velocity of the host star cluster, the remnant MBH is thought to be ejected from the cluster, and its host cluster mass is labeled as zero.

Comparison with Other Seeding Models

The study compares three seeding models: star-cluster-based (SC-noR), gas-based (G-noR), and halo-based (H-noR).

The star-cluster model produces more MBH seeds within the same DM-FOF halo because multiple MBHs can form in situ within a single halo, leading to a spatially clustered population.

The SC-noR run produces about half an order of magnitude more MBH seeds than G-noR by z = 6.

The star-cluster model correlates both the abundance and mass of MBHs with their local environments, providing a more physically motivated framework for predicting MBH populations in dwarf galaxies.

Conclusion

The star-cluster-based seeding model produces a strong connection between MBHs and their host environments, where massive seeds form preferentially in massive, compact, and metal-poor star clusters.

The model predicts a gradual increase in the MBH occupation fraction focc with total halo mass and halo stellar mass.

The star-cluster-based seeding model produces more abundant MBHs within the same DM-FOF halo because multiple MBHs can form in situ within a single halo.

The resulting Mseed distribution appears as a power-law distribution with a slope of −1, similar to the seed mass distribution adopted in the simulations AMBRA and ASTRID, while shifted to lower mass.

The star-cluster-based seeding model produces a strong connection between MBHs and their host environments, both the number of MBHs and central MBH masses increase systematically with galaxy masses.

Improvements for AI systems

Improved MBH seeding model for cosmological simulations: The new subgrid model develop[s] a new subgrid model for the stellar-cluster seeding pathway in cosmological hydrodynamic simulations, in which the formation and evolution of unresolved dense star clusters are explicitly modeled, allowing researchers to establish a physically motivated connection between galaxy formation and massive black hole seed formation through the stellar-cluster pathway.
Enhanced LISA event rate prediction: The model is implemented in a constrained simulation where Multiple MBHs are naturally allowed to form in situ within individual halos, producing a spatially clustered population, which increases the MBH merger rate by ∼ 100 relative to other seeding models, significantly enhancing the expected LISA event rate.
Improved low-mass seed detection: TDEs can be used as a probe because they can dominate the growth of 103−4 M⊙ MBHs and produce luminous flares of Lpeak ∼ 10 42−43 erg s−1, increasing the observability of low-mass seeds.
More physically motivated scaling relations: The model provides a more physical MBH−Mgalaxy scaling for low-mass galaxies (Mgalaxy ∼ 10 6−9 M⊙), a regime poorly described by previous seeding models, as the seed mass is determined self-consistently from its host star cluster.
Constrained environment comparison: The simulation allows for a controlled comparison between seeding models rather than to provide a statistical prediction for the cosmological MBH population, enabling direct testing of different physical prescriptions in extreme overdense regions.
Redshift evolution tracking: The model tracks the evolution of the central MBH, showing that "the rapid growth in SC-noR is particularly interesting because compared to the G-noR run, it starts from a much less massive seed (log Mseed = 4.18 versus log Mseed = 5.32) at a much later redshift (zseed = 12 versus zseed = 18.6)."
GW recoil impact assessment: The model allows for testing the effect of GW recoil by comparing runs with and without the GW recoil, enabling researchers to observe how the early growth of the MBHs (z≳ 9) is delayed when recoil is implemented.

Abstract

JWST has revealed massive star clusters at z 6, which provide promising environments for massive black hole (MBH) seed formation. We introduce a new MBH seeding model for cosmological simulations, physically motivated by the runaway collisions in star clusters. Subgrid star clusters are generated according to the local ISM and evolved through stellar evolution and two-body relaxation. The masses of MBH seeds formed through runaway collisions are determined by the properties of their host clusters, including the effects of metallicity-dependent stellar winds. We further follow tidal disruption events (TDEs) with the evolving clusters, which can be enhanced in MBH binaries, and account for gravitational-wave (GW) recoil following MBH mergers. We implement this model in a constrained simulation of a 5 σ overdense region, where seeds of 10 cubed-10 5.6,M form in clusters with 10 4 at most m SC at most 10 8,M. Because both the seed abundance and mass are directly connected to the local environment, we have a more physical M BH!-!M galaxy scaling for low-mass galaxies (M galaxy about10 6-9,M), a regime poorly described by previous seeding models. Multiple MBHs are naturally allowed to form in-situ within individual halos, producing a spatially clustered population. This increases the MBH merger rate by about100 relative to other seeding models, significantly enhancing the expected LISA event rate. TDEs can dominate the growth of 10 3-4,M MBHs and produce luminous flares of L peak about 10 42-43, erg,s-1, increasing the observability of low-mass seeds. This seeding prescription accelerates early MBH growth at z 8, while subsequent self-regulated gas accretion drives the central MBH toward similar masses about10 8.6, M by z=6 across different seeding models.