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Record W2589738005 · doi:10.3847/2041-8213/aa667d

Ultra-diffuse and Ultra-compact Galaxies in the Frontier Fields Cluster Abell 2744

2017· article· en· W2589738005 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal Letters · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsCanadian Institute for Theoretical Astrophysics
Fundersnot available
KeywordsGlobular clusterGalaxyGalaxy clusterAbell 2744Cluster (spacecraft)PopulationGalaxy groups and clusters

Abstract

fetched live from OpenAlex

Abstract We report the discovery of a large population of ultra-diffuse galaxies (UDGs) in the massive galaxy cluster Abell 2744 ( z = 0.308) as observed by the Hubble Frontier Fields program. Since this cluster is ∼5 times more massive than Coma, our observations allow us to extend 0.7 dex beyond the high-mass end of the relationship between UDG abundance and cluster mass reported by van der Burg et al. Using the same selection criteria as van der Burg et al., A2744 hosts an estimated 1961 ± 577 UDGs, 10 times the number in Coma. As noted by Lee & Jang, A2744 contains numerous unresolved compact objects, which those authors identified predominantly as globular clusters. However, these objects have luminosities that are more consistent with ultra-compact dwarf (UCD) galaxies. The abundances of both UCDs and UDGs scale with cluster mass as a power law with a similar exponent, although UDGs and UCDs have very different radial distributions within the cluster. The radial surface density distribution of UCDs rises sharply toward the cluster center, while the surface density distribution of the UDG population is essentially flat. Together, these observations hint at a picture where some UCDs in A2744 may have once been associated with infalling UDGs. As UDGs fall in and dissolve, they leave behind a residue of unbound UCDs.

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 score0.022
Threshold uncertainty score0.764

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 studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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

Citations73
Published2017
Admission routes1
Has abstractyes

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