THE ACS FORNAX CLUSTER SURVEY. IX. THE COLOR-MAGNITUDE RELATION OF GLOBULAR CLUSTER SYSTEMS
Bibliographic record
Abstract
We investigate the color–magnitude relation for globular clusters (GCs)—the so-called blue tilt—detected in the Advanced Camera for Surveys (ACS) Fornax Cluster Survey and using the combined sample of GCs from the ACS Fornax and Virgo Cluster Surveys. We find a tilt of γ z ≡ d ( g − z )/ dz = −0.0257 ± 0.0050 for the full GC sample of the Fornax Cluster Survey (≈5800 GCs). This is slightly shallower than the value γ z = −0.0459 ± 0.0048 found for the Virgo Cluster Survey GC sample (≈11,100 GCs). The slope for the merged Fornax and Virgo data sets (≈16,900 GCs) is γ z = −0.0293 ± 0.0085, corresponding to a mass–metallicity relation of Z ∝ M 0.43±0.12 . We find that the blue tilt sets in at masses in excess of M ∼ 2 × 10 5 M ☉ . The tilt is stronger for GCs belonging to high-mass galaxies ( M * ≳ 5 × 10 10 M ☉ ) than for those in low-mass galaxies ( M * ≲ 5 × 10 10 M ☉ ). It is also more pronounced for GCs with smaller galactocentric distances. Our findings suggest a range of mass–metallicity relations Z GC ∝ M 0.3–0.7 GC which vary as a function of host galaxy mass/luminosity, a scaling similar to that observed for dwarf spheroidal galaxies. We compare our observations to a recent model of star cluster self-enrichment with generally favorable results. We suggest that, within the context of this model, the protocluster clouds out of which the GCs formed may have had density profiles slightly steeper than isothermal and/or star formation efficiencies somewhat below 0.3. We caution, however, that the significantly different appearance of the color–magnitude diagrams (CMDs) defined by the GC systems associated with galaxies of similar mass and morphological type poses a challenge to any single mechanism, including self-enrichment, that seeks to explain generically the observed GC color–magnitude relations. We therefore suggest that the detailed (and stochastic) merger/accretion histories of individual galaxies have likely played a non-negligible role determining the distribution of GCs in the CMDs of individual GC systems.
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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 | 0.003 |
| Science and technology studies | 0.000 | 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) | 0.008 | 0.005 |
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".