THE RICH GLOBULAR CLUSTER SYSTEM OF ABELL 1689 AND THE RADIAL DEPENDENCE OF THE GLOBULAR CLUSTER FORMATION EFFICIENCY
Bibliographic record
Abstract
We study the rich globular cluster (GC) system in the center of the massive cluster of galaxies Abell 1689 ( z = 0.18), one of the most powerful gravitational lenses known. With 28 Hubble Space Telescope /Advanced Camera for Surveys orbits in the F814W bandpass, we reach a magnitude I 814 = 29 with ≳90% completeness and sample the brightest ∼5% of the GC system. Assuming the well-known Gaussian form of the GC luminosity function (GCLF), we estimate a total population of GCs within a projected radius of 400 kpc. As many as half of the GCs may comprise an intracluster component. Even with the sizable uncertainties, which mainly result from the uncertain GCLF parameters, this system is by far the largest GC population studied to date. The specific frequency S N is high, but not uncommon for central galaxies in massive clusters, rising from S N ≈ 5 near the center to ∼12 at large radii. Passive galaxy fading would increase S N by ∼20% at z = 0. We construct the radial mass profiles of the GCs, stars, intracluster gas, and lensing-derived total mass, and we compare the mass fractions as a function of radius. The estimated mass in GCs, = 3.9 × 10 10 M ☉ , is comparable to ∼80% of the total stellar mass of the Milky Way. The shape of the GC mass profile appears intermediate between those of the stellar light and total cluster mass. Despite the extreme nature of this system, the ratios of the GC mass to the baryonic and total masses, and thus the GC formation efficiency, are typical of those in other rich clusters when comparing at the same physical radii. The GC formation efficiency is not constant, but varies with radius, in a manner that appears similar for different clusters; we speculate on the reasons for this similarity in profile.
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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 | 0.001 | 0.000 |
| 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".