Specific Frequencies and Luminosity Profiles of Cluster Galaxies and Intracluster Light in Abell 1689
Bibliographic record
Abstract
Abstract We present magnitudes and profile fits for 180 galaxies in the central field of the massive lensing cluster Abell 1689 using very deep imaging with the Hubble Space Telescope Advanced Camera for Surveys in the F814W bandpass. Previous work revealed an exceptionally large number of globular clusters (GCs) in A1689 and mapped their number density distribution. We decompose this number density map into GCs associated with individual cluster galaxies and ICGCs (intracluster GCs) associated with the intracluster light (ICL). In all, we measure GC specific frequencies S N for 33 cluster members and the ICL. The relation between S N and galaxy magnitude is consistent with the trend observed in Virgo, although some intermediate-luminosity galaxies scatter to S N > 10 . We estimate that the ICL makes up 11% of the starlight in this field, whereas the ICGCs account for ∼35% of the GCs, both consistent with predictions from simulations. Galaxies with higher S N values tend to be rounder, and there is a marginally significant trend of decreasing S N with increasing specific angular momenta λ R . We also reevaluate the GC population in the A2744 Frontier Field, for which fewer than 1/10 as many GCs have been detected because of its larger distance. Finally, our core-Sérsic fit to the light profile of the A1689 brightest cluster galaxy implies a break radius of 3.8 kpc, among the largest known; we discuss implications of the sizable core and extensive GC population for the supermassive black hole in light of scaling relations.
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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 | 0.000 |
| 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 | 0.001 |
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".