The Globular Cluster Systems of Ultra-diffuse Galaxies in the Coma Cluster
Bibliographic record
Abstract
Abstract Ultra-diffuse galaxies (UDGs) are unusual galaxies with low luminosities, similar to classical dwarf galaxies, but with sizes up to ∼5 larger than expected for their mass. Some UDGs have large populations of globular clusters (GCs), something unexpected in galaxies with such low stellar density and mass. We have carried out a comprehensive study of GCs in both UDGs and classical dwarf galaxies at comparable stellar masses using Hubble Space Telescope (HST) observations of the Coma cluster. We present new imaging for 33 Dragonfly UDGs with the largest effective radii (>2 kpc), and additionally include 15 UDGs and 54 classical dwarf galaxies from the HST/ACS Coma Treasury Survey and the literature. Out of a total of 48 UDGs, 27 have statistically significant GC systems, and 11 have candidate nuclear star clusters. The GC specific frequency (S N ) varies dramatically, with the mean S N being higher for UDGs than for classical dwarfs. At constant stellar mass, galaxies with larger sizes (or lower surface brightnesses) have higher S N , with the trend being stronger at higher stellar mass. At lower stellar masses, UDGs tend to have higher S N when closer to the center of the cluster, i.e., in denser environments. The fraction of UDGs with a nuclear star cluster also depends on environment, varying from ∼40% in the cluster core, where it is slightly lower than the nucleation fraction of classical dwarfs, to ≲20% in the outskirts. Collectively, we observe an unmistakable diversity in the abundance of GCs, and this may point to multiple formation routes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".