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The formation of star clusters - I. Three-dimensional simulations of hydrodynamic turbulence

2004· article· en· W1959965095 on OpenAlexaff
David A. Tilley, Ralph E. Pudritz

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPhysicsTurbulenceGravitational collapseAstrophysicsAngular momentumStructure formationStar formationMolecular cloudCluster (spacecraft)Star clusterGravitationClassical mechanicsStarsMechanicsGalaxy

Abstract

fetched live from OpenAlex

We present the results of a series of numerical simulations of compressible, self-gravitating hydrodynamic turbulence of cluster-forming clumps in molecular clouds. We examine the role that turbulence has in the formation of gravitationally bound cores, studying the dynamical state, internal structure and bulk properties of these cores. Complex structure in turbulent clumps is formed provided that the damping time of the turbulence, tdamp, is longer than the gravitational free-fall time tff in a region. We find a variety of density and infall velocity structures among the cores in the simulation, including cores that resemble the Larson–Penston collapse of an isothermal sphere (ρ∝r−2) and cores that resemble the McLaughlin–Pudritz collapse of logatropic spheres (ρ∝r−1). The specific angular momentum profiles range between j∝r1−r2. The masses of the bound cores that form fit the initial mass function, while the specific angular momentum distribution can be fit by a broken power law. While our hydrodynamic simulations reproduce many of the observed properties of cores, we find an upper limit for the star formation efficiency in clusters of 40–50 per cent.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Simulation or modelinglow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Simulation or modelinglow
models agreeAgreement compares identical category sets and study designs across arms.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.295

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 integrity0.0000.000
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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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

Labeled directly by 2 models reading the full record.

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

Citations87
Published2004
Admission routes1
Has abstractyes

Explore more

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