Revisiting the stellar velocity ellipsoid–Hubble-type relation: observations versus simulations
Bibliographic record
Abstract
The stellar velocity ellipsoid (SVE) in galaxies can provide important information on the processes that participate in the dynamical heating of their disc components (e.g. giant molecular clouds, mergers, spiral density waves, and bars). Earlier findings suggested a strong relation between the shape of the disc SVE and Hubble type, with later-type galaxies displaying more anisotropic ellipsoids and early types being more isotropic. In this paper, we revisit the strength of this relation using an exhaustive compilation of observational results from the literature on this issue. We find no clear correlation between the shape of the disc SVE and morphological type, and show that galaxies with the same Hubble type display a wide range of vertical-to-radial velocity dispersion ratios. The points are distributed around a mean value and scatter of σz/σR = 0.7 ± 0.2. With the aid of numerical simulations, we argue that different mechanisms might influence the shape of the SVE in the same manner and that the same process (e.g. mergers) does not have the same impact in all the galaxies. The complexity of the observational picture is confirmed by these simulations, which suggest that the vertical-to-radial axis ratio of the SVE is not a good indicator of the main source of disc heating. Our analysis of those simulations also indicates that the observed shape of the disc SVE may be affected by several processes simultaneously and that the signatures of some of them (e.g. mergers) fade over time.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".