Contribution of stripped nuclei to the ultracompact dwarf galaxy population in the Virgo cluster
Bibliographic record
Abstract
ABSTRACT We use the hydrodynamical EAGLE simulation to predict the numbers, masses, and radial distributions of tidally stripped galaxy nuclei in massive galaxy clusters, and compare these results to observations of ultracompact dwarf galaxies (UCDs) in the Virgo cluster. We trace the merger trees of galaxies in massive galaxy clusters back in time and determine the numbers and masses of stripped nuclei from galaxies disrupted in mergers. The spatial distribution of stripped nuclei in the simulations is consistent with those of UCDs surrounding massive galaxies in the Virgo cluster. Additionally, the numbers of stripped nuclei are consistent with the numbers of M > 107 M⊙ UCDs around individual galaxies and in the Virgo cluster as a whole. The mass distributions in this mass range are also consistent. We find that the numbers of stripped nuclei surrounding individual galaxies correlate better with the stellar or halo mass of individual galaxies than the total cluster mass. We conclude that most high mass (M > 107 M⊙) UCDs are likely stripped nuclei. It is difficult to draw reliable conclusions about low mass (M < 107 M⊙) UCDs because of observational selection effects. We additionally predict that a few hundred stripped nuclei below a mass of 2 × 106 M⊙ should exist in massive galaxies that will overlap in mass with the globular cluster population. Approximately 1–3 stripped nuclei in the process of forming also exist per massive galaxy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".