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Record W3044528833 · doi:10.1093/mnras/staa2122

Formation of counter-rotating stars during gas-rich disc–disc mergers

2020· article· en· W3044528833 on OpenAlexafffund
Hugo Martel, Simon Richard

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversité LavalCentre for Research in Astrophysics of Québec
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsStarsAstrophysicsBulgeVelocity dispersionGalaxyStar formationDisc galaxyAstronomyGalaxy formation and evolution

Abstract

fetched live from OpenAlex

ABSTRACT We present a new scenario for the origin of the counter-rotating stars in disc galaxies, defined as stars that have a negative tangential velocity. This scenario involves a merger between two gas-rich disc galaxies that have comparable masses, are nearly coplanar, and are rotating in the same direction. The merger results in an intense starburst, during which a significant fraction of the gas is converted to stars. The system then settles into an equilibrium configuration consisting of a thick disc and a bulge partly supported by velocity dispersion and a thin disc supported by rotation. Star formation proceeds until most of the gas supply is exhausted. Stars formed during the starburst have tangential velocities ranging from $-600$ to $600\, {\rm km\, s^{-1}}$. Stars formed afterward in the thick disc and bulge have high eccentricities and low tangential velocities, typically in the range $-100$ to $100\, {\rm km\, s^{-1}}$, while stars formed in the thin disc have large, positive velocities. All fast, counter-rotating stars ($V\lt -200\, {\rm km\, s^{-1}}$) are old, metal-poor, with very low dispersion in ages and metallicities. By contrast, fast, corotating stars ($V\gt 200\, {\rm km\, s^{-1}}$) have a wide range of ages and metallicities. The average abundances ratios $\rm [O/H]$ and [Fe/H] for fast, corotating stars typically exceed the corresponding ratios for fast, counter-rotating stars by $0.1-0.4\,\mathrm{ dex}$, while the dispersion in the values of NFe/NH are larger by factors between 2 and 14. This provides an observational signature of major, gas-rich mergers at high redshift.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.191
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

Citations7
Published2020
Admission routes2
Has abstractyes

Explore more

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