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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 of the first candidate BH-WD X-ray binaries, where the compact accretors may be stellar-mass black hole candidates in extragalactic globular clusters, 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 to form BH-WD binaries is via coupling these usual formation channels with subsequent hardening and/or triple formation. Indeed, we find that the most important mechanism to make a BH-WD X-ray binary from an initially dynamically formed BH-WD binary is triple induced mass transfer via the Kozai mechanism. Even using the most optimistic estimates for the formation rates, we cannot match the observationally inferred production rates if black holes undergo significant evaporation from the cluster or form a completely detached subcluster of black holes. We estimate that at least 1% of all formed black holes, or presumably 10% of the black holes 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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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