Ultra-diffuse galaxies in the perseus cluster: comparing galaxy properties with globular cluster system richness
Bibliographic record
Abstract
ABSTRACT It is clear that within the class of ultra-diffuse galaxies (UDGs), there is an extreme range in the richness of their associated globular cluster (GC) systems. Here, we report the structural properties of five UDGs in the Perseus cluster based on deep Subaru/Hyper Suprime-Cam imaging. Three appear GC-poor and two appear GC-rich. One of our sample, PUDG_R24, appears to be undergoing quenching and is expected to fade into the UDG regime within the next ∼0.5 Gyr. We target this sample with Keck Cosmic Web Imager (KCWI) spectroscopy to investigate differences in their dark matter haloes, as expected from their differing GC content. Our spectroscopy measures both recessional velocities, confirming Perseus cluster membership, and stellar velocity dispersions, to measure dynamical masses within their half-light radius. We supplement our data with that from the literature to examine trends in galaxy parameters with GC system richness. We do not find the correlation between GC numbers and UDG phase space positioning expected if GC-rich UDGs environmentally quench at high redshift. We do find GC-rich UDGs to have higher velocity dispersions than GC-poor UDGs on average, resulting in greater dynamical mass within the half-light radius. This agrees with the first order expectation that GC-rich UDGs have higher halo masses than GC-poor UDGs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".