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Record W2015740981 · doi:10.1134/s1063772910100021

Cooling and fragmentation of gas in rotating protogalaxies

2010· article· en· W2015740981 on OpenAlexaff
E. O. Vasiliev, Eduard I. Vorobyov, Yu. A. Shchekinov

Bibliographic record

VenueAstronomy Reports · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsPhysicsAngular momentumAstrophysicsStarsProtogalaxyGalaxySpecific relative angular momentumDark matterRedshiftBaryonGalaxy formation and evolutionFragmentation (computing)Total angular momentum quantum numberAngular momentum couplingClassical mechanicsGalaxy merger

Abstract

fetched live from OpenAlex

The dynamical, thermal, and chemical evolution of gas in protogalaxies with non-zero angular momentum is considered. It is shown that, in protogalaxies with a total mass (dark and baryonic) of M = 107 M⊙ at redshifts z = 12 whose gas has rotational angular momentum (spin parameter λ ≳ 0.005), a disk-like structure forms during the initial collapse of the galaxy, in contrast to non-rotating protogalaxies, whose collapse is spherically symmetric. The existence of initial angular momentumfor gas in protogalaxies increases the cooling time of the gas, delaying the formation of the first stars. Increasing the rotational angular momentum of the gas leads to cooling of the gas to lower temperatures (T < 100 K), at which HD molecules dominate in the cooling, while the total mass of cool gas (T < 1000 K) is decreased. The stability of disk-like structures in the central regions of protogalaxies is analyzed. It is shown that the disk that is formed is gravitationally unstable, and multiple fragmentation at various distances from the center is possible when the initial rotational angular momentum of the protogalaxy is increased. The possible birth of several stars in the first protogalaxies is discussed.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.004
GPT teacher head0.242
Teacher spread0.238 · 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

Citations5
Published2010
Admission routes1
Has abstractyes

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