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Record W2794449838 · doi:10.3847/2041-8213/aab60b

An Enigmatic Population of Luminous Globular Clusters in a Galaxy Lacking Dark Matter

2018· article· en· W2794449838 on OpenAlexaff
Pieter van Dokkum, Yotam Cohen, Shany Danieli, J. M. Diederik Kruijssen, Aaron J. Romanowsky, Allison Merritt, Roberto Abraham, Jean P. Brodie, Charlie Conroy, Deborah Lokhorst, Lamiya Mowla, Ewan O’Sullivan, Jielai Zhang

Bibliographic record

VenueThe Astrophysical Journal Letters · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGlobular clusterDark matterAstrophysicsPhysicsAstronomyGalaxy

Abstract

fetched live from OpenAlex

Abstract We recently found an ultra diffuse galaxy (UDG) with a half-light radius of R e = 2.2 kpc and little or no dark matter. The total mass of NGC1052–DF2 was measured from the radial velocities of bright compact objects that are associated with the galaxy. Here, we analyze these objects using a combination of Hubble Space Telescope ( HST ) imaging and Keck spectroscopy. Their average size is pc and their average ellipticity is . From a stacked Keck spectrum we derive an age of ≳9 Gyr and a metallicity of [Fe/H] = −1.35 ± 0.12. Their properties are similar to ω Centauri, the brightest and largest globular cluster in the Milky Way, and our results demonstrate that the luminosity function of metal-poor globular clusters is not universal. The fraction of the total stellar mass that is in the globular cluster system is similar to that in other UDGs, and consistent with “failed galaxy” scenarios, where star formation terminated shortly after the clusters were formed. However, the galaxy is a factor of ∼1000 removed from the relation between globular cluster mass and total galaxy mass that has been found for other galaxies, including other UDGs. We infer that a dark matter halo is not a prerequisite for the formation of metal-poor globular cluster-like objects in high-redshift galaxies.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.542

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 communication0.0000.001
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 head0.006
GPT teacher head0.217
Teacher spread0.211 · 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 designObservational
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

Citations106
Published2018
Admission routes1
Has abstractyes

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