THE ADVANCED CAMERA FOR SURVEYS FORNAX CLUSTER SURVEY. VII. HALF-LIGHT RADII OF GLOBULAR CLUSTERS IN EARLY-TYPE GALAXIES
Bibliographic record
Abstract
We measure the half-light radii of globular clusters (GCs) in 43 galaxies from the Advanced Camera for Surveys (ACS) Fornax Cluster Survey. We use these data to extend previous work in which the environmental dependencies of the half-light radii of GCs in early-type galaxies in the ACS Virgo Cluster Survey were studied, and a corrected mean half-light radius (corrected for the observed environmental trends) was suggested as a reliable distance indicator. This work both increases the sample size for the study of the environmental dependencies, and adds leverage to the study of the corrected half-light radius as a possible distance indicator (since Fornax lies at a larger distance than the Virgo cluster). We study the environmental dependencies of the size of GCs using both a Principal Component Analysis as well as two-dimensional scaling relations. We largely confirm the environmental dependencies shown in Jordán et al., but find evidence that there is a residual correlation in the mean half-light radius of GC systems with galaxy magnitude, and subtle differences in the other correlations—so there may not be a universal correction for the half-light radii of lower luminosity galaxy GC systems. The main factor determining the size of a GC in an early-type galaxy is the GC color. Red GCs have 〈 r h 〉 = 2.8 ± 0.3 pc, while blue GCs have 〈 r h 〉 = 3.4 ± 0.3 pc. We show that for bright early-type galaxies ( M B < −19 mag), the uncorrected mean half-light radius of the GC system is by itself an excellent distance indicator (with error ∼11%), having the potential to reach cosmologically interesting distances in the era of high angular resolution adaptive optics on large optical telescopes.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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".