Deep CCD Surface Photometry of Galaxy Clusters. II. Searching for Intracluster Starlight in Non‐cD clusters
Bibliographic record
Abstract
We report the search for intracluster light in four Abell type II-III (non-cD) galaxy clusters: A801, A1234, A1553, and A1914. We find that on average these clusters contain ~10% of their detected stellar luminosity in a diffuse component. We show that for two of the clusters the intracluster light closely follows the galaxy distribution, but in the other two cases, there are noticeable differences between the spatial distribution of the galaxies and the intracluster light. We report the results of a search for intracluster tidal debris in each cluster and note that A1914 in particular has a number of strong tidal features likely due to its status as a recent cluster merger. One of the A1914 features appears to be spatially coincident with an extension seen in weak lensing maps, implying that the feature traces a large amount of mass. We compare these results with numerical simulations of hierarchically formed galaxy clusters and find good general agreement between the observed and simulated images, although we also find that our observations sample only the brightest features of the intracluster light. Together, these results suggest that intracluster light can be a valuable tool in determining the evolutionary state of galaxy clusters.
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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 | 0.001 |
| 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) | 0.003 | 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".