Galactic kinematics and dynamics from Radial Velocity Experiment stars
Bibliographic record
Abstract
We analyse the kinematics of ∼400 000 stars that lie within ∼2 kpc of the Sun and have spectra measured in the Radial Velocity Experiment. We decompose the sample into hot and cold dwarfs, red-clump and non-clump giants. The kinematics of the clump giants are consistent with being identical with those of the giants as a whole. Without binning the data we fit Gaussian velocity ellipsoids to the meridional-plane components of velocity of each star class and give formulae from which the shape and orientation of the velocity ellipsoid can be determined at any location. The data are consistent with the giants and the cool dwarfs sharing the same velocity ellipsoids, which have vertical velocity dispersion rising from 21 km s−1 in the plane to ∼55 km s−1 at |z| = 2 kpc and radial velocity dispersion rising from 37 km s−1 to 82 km s−1 in the same interval. At (R, z), the longest axis of one of these velocity ellipsoids is inclined to the Galactic plane by an angle ∼0.8 arctan(z/R). We use a novel formula to obtain precise fits to the highly non-Gaussian distributions of vϕ components in eight bins in the (R, z) plane. We compare the observed velocity distributions with the predictions of a published dynamical model fitted to the velocities of stars that lie within ∼150 pc of the Sun and star counts towards the Galactic pole. The predictions for the vz distributions are exceptionally successful. The model's predictions for vϕ are successful except for the hot dwarfs, and its predictions for vr fail significantly only for giants that lie far from the plane. If distances to the model's stars are overestimated by 20 per cent, the predicted distributions of vr and vz components become skew, and far from the plane broader. The broadening significantly improves the fits to the data. The ability of the dynamical model to give such a good account of a large body of data to which it was not fitted inspires confidence in the fundamental correctness of the assumed, disc-dominated, gravitational potential.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".