Kinematics with Gaia DR2: the force of a dwarf
Bibliographic record
Abstract
ABSTRACT We use Gaia DR2 astrometric and line-of-sight velocity information combined with two sets of distances obtained with a Bayesian inference method to study the 3D velocity distribution in the Milky Way disc. We search for variations in all Galactocentric cylindrical velocity components (Vϕ, VR, and Vz) with Galactic radius, azimuth, and distance from the disc mid-plane. We confirm recent work showing that bulk vertical motions in the R–z plane are consistent with a combination of breathing and bending modes. In the x–y plane, we show that, although the amplitudes change, the structure produced by these modes is mostly invariant as a function of distance from the plane. Comparing to two different Galactic disc models, we demonstrate that the observed patterns can drastically change in short time intervals, showing the complexity of understanding the origin of vertical perturbations. A strong radial VR gradient was identified in the inner disc, transitioning smoothly from 16 km s−1 kpc−1 at an azimuth of 30° < ϕ < 45° ahead of the Sun-Galactic centre line to −16 km s−1 kpc−1 at an azimuth of −45° < ϕ < −30° lagging the solar azimuth. We use a simulation with no significant recent mergers to show that exactly the opposite trend is expected from a barred potential, but overestimated distances can flip this trend to match the data. Alternatively, using an N-body simulation of the Sagittarius dwarf–Milky Way interaction, we demonstrate that a major recent perturbation is necessary to reproduce the observations. Such an impact may have strongly perturbed the existing bar or even triggered its formation in the last 1–2 Gyr.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".