The dynamical state of bars in cluster dwarf galaxies: The cases of NGC 4483 and NGC 4516
Bibliographic record
Abstract
Dwarf barred galaxies are the perfect candidates for hosting slowly-rotating bars. They are common in dense environments and they have a relatively shallow potential well, making them prone to heating by interactions. When an interaction induces bar formation, the bar should rotate slowly. They reside in massive and centrally-concentrated dark matter halos, which slow down the bar rotation through dynamical friction. While predictions suggest that slow bars should be common, measurements of bar pattern speed, using the Tremaine-Weinberg method, show that bars are mostly fast in the local Universe. We present a photometric and kinematic characterisation of bars hosted by two dwarf galaxies in the Virgo Cluster, NGC 4483 and NGC 4516. We derive the bar length and strength using the Next Generation Virgo Survey imaging and the circular velocity, bar pattern speed, and rotation rate using spectroscopy from the Multi Unit Spectroscopic Explorer. Including the previously studied galaxy IC 3167, we compare the bar properties of the three dwarf galaxies with those of their massive counterparts from literature. Bars in the dwarf galaxies are shorter and weaker, and rotate slightly slower with respect to those in massive galaxies. This could be due to a different bar formation mechanism and/or to a large dark matter fraction in the centre of dwarf galaxies. We show that it is possible to push the application of the Tremaine-Weinberg method to the galaxy low mass regime.
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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 | 0.001 |
| 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) | 0.001 | 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".