Evidence of Absence of Tidal Features in the Outskirts of Ultra Diffuse Galaxies in the Coma Cluster
Bibliographic record
Abstract
Abstract We study the presence of tidal features associated with ultra diffuse galaxies (UDGs) in galaxy clusters. Specifically, we stack deep Subaru images of UDGs in the Coma cluster to determine whether they show position angle twists at large radii. Selecting galaxies with central surface brightness magarcsec−2 and projected half-light radius , we identify 287 UDGs in the Yagi et al. catalog of low surface brightness Coma objects. The UDGs have apparent spheroidal shapes with median Sérsic index and median axis ratio . The images are processed by masking all background objects and rotating to align the major axis before stacking them in bins of properties such as axis ratio, angle of major axis with respect to the cluster center, and separation from cluster center. Our image stacks reach further than 7 kpc (≳4r e). Analysis of the isophotes of the stacks reveals that the ellipticity remains constant up to the last measured point, which means that the individual galaxies have a non-varying position angle and axis ratio and show no evidence for tidal disruption out to . We demonstrate this explicitly by comparing our stacks with stacks of model UDGs with and without tidal features in their outskirts. We infer that the average tidal radius of the Coma UDGs is >7 kpc and estimate that the average dark matter fraction within the tidal radius of the UDGs inhabiting the innermost 0.5 Mpc of Coma is >99%.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".