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Record W2128469357 · doi:10.1093/mnras/stu1437

On the coexistence of stellar-mass and intermediate-mass black holes in globular clusters

2014· article· en· W2128469357 on OpenAlexaff
Nathan W. C. Leigh, Nora Lützgendorf, Aaron M. Geller, Thomas J. Maccarone, C. O. Heinke, Alberto Sesana

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGlobular clusterPhysicsAstrophysicsBlack hole (networking)Intermediate-mass black holeStar clusterAstronomyStellar massMass segregationCluster (spacecraft)Binary black holeGravitational waveGalaxyStar formation

Abstract

fetched live from OpenAlex

In this paper, we address the question: what is the probability of stellar-mass black hole (BH) binaries co-existing in a globular cluster with an intermediate-mass black hole (IMBH)? Our results suggest that the detection of one or more BH binaries can strongly constrain the presence of an IMBH in most Galactic globular clusters. More specifically, the detection of one or more BH binaries could strongly indicate against the presence of an IMBH more massive than ≳103 M⊙ in roughly 80 per cent of the clusters in our sample. To illustrate this, we use a combination of N-body simulations and analytic methods to weigh the rate of formation of BH binaries against their ejection and/or disruption rate via strong gravitational interactions with the central (most) massive BH. The eventual fate of a sub-population of stellar-mass BHs (with or without binary companions) is for all BHs to be ejected from the cluster by the central IMBH, leaving only the most massive stellar-mass BH behind to form a close binary with the IMBH. During each phase of evolution, we discuss the rate of inspiral of the central BH–BH pair as a function of both the properties of the binary and its host cluster.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.190
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations90
Published2014
Admission routes1
Has abstractyes

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Same venueMonthly Notices of the Royal Astronomical SocietySame topicGalaxies: Formation, Evolution, PhenomenaFrench-language works237,207