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Record W2787671113 · doi:10.3847/2041-8213/aaaeb4

Declining Rotation Curves at z = 2 in ΛCDM Galaxy Formation Simulations

2018· article· en· W2787671113 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal Letters · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsGalaxy rotation curveDark matterGalaxyGalaxy formation and evolutionDark galaxyCold dark matterDiscDwarf galaxy problemRotation (mathematics)

Abstract

fetched live from OpenAlex

Abstract Selecting disk galaxies from the cosmological, hydrodynamical simulation Magneticum Pathfinder, we show that almost half of our poster child disk galaxies at z = 2 show significantly declining rotation curves and low dark matter fractions, very similar to recently reported observations. These galaxies do not show any anomalous behavior, they reside in standard dark matter halos, and they typically grow significantly in mass until z = 0, where they span all morphological classes, including disk galaxies matching present-day rotation curves and observed dark matter fractions. Our findings demonstrate that declining rotation curves and low dark matter fractions in rotation-dominated galaxies at z = 2 appear naturally within the ΛCDM paradigm and reflect the complex baryonic physics, which plays a role at the peak epoch of star formation. In addition, we find some dispersion-dominated galaxies at z = 2 that host a significant gas disk and exhibit similar shaped rotation curves as the disk galaxy population, rendering it difficult to differentiate between these two populations with currently available observation techniques.

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)0.001
metaresearch head score (Gemma)0.004
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.012
GPT teacher head0.240
Teacher spread0.229 · 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

Citations23
Published2018
Admission routes1
Has abstractyes

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