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Record W2034961162 · doi:10.1088/0004-637x/717/2/948

FORMATION OF BLACK HOLE X-RAY BINARIES IN GLOBULAR CLUSTERS

2010· article· en· W2034961162 on OpenAlexaff
Natalia Ivanova, S. Chaichenets, John M. Fregeau, C. O. Heinke, James C. Lombardi, Tyrone E. Woods

Bibliographic record

VenueThe Astrophysical Journal · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGlobular clusterPhysicsAstrophysicsBlack hole (networking)Intermediate-mass black holeBinary numberMass segregationStar clusterPopulationCluster (spacecraft)Binary black holeStellar black holeStarsAstronomyGalaxyGravitational wave

Abstract

fetched live from OpenAlex

Inspired by the recent identification in extragalactic globular clusters of the first candidate black hole–white dwarf (BH–WD) X-ray binaries, where the compact accretors may be stellar-mass black holes (BHs), we explore how such binaries could be formed in a dynamical environment. We provide analyses of the formation rates via well-known formation channels like binary exchange and physical collisions and propose that the only possibility of forming BH–WD binaries is via coupling these usual formation channels with subsequent hardening and/or triple formation. In particular, we find that the most important mechanism for the creation of a BH–WD X-ray binary from an initially dynamically formed BH–WD binary is mass transfer induced in a triple system via the Kozai mechanism. Furthermore, we find that BH–WD binaries that evolve into X-ray sources can be formed by exchanges of a BH into a WD–WD binary or possibly by collisions of a BH and a giant star. If BHs undergo significant evaporation from the cluster or form a completely detached subcluster of BHs, then we cannot match the observationally inferred production rates even using the most optimistic estimates of formation rates. To explain the observations with stellar-mass BH–WD binaries, at least 1% of all formed BHs, or presumably 10% of the BHs present in the core now, must be involved in interactions with the rest of the core stellar population.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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 designObservational
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

Citations92
Published2010
Admission routes1
Has abstractyes

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