THE IMPRINT OF RADIAL MIGRATION ON THE VERTICAL STRUCTURE OF GALAXY DISKS
Bibliographic record
Abstract
ABSTRACT We use numerical simulations to examine the effects of radial migration on the vertical structure of galaxy disks. The simulations follow three exponential disks of different mass but similar circular velocity, radial scalelength, and (constant) scale height. The disks develop different non-axisymmetric patterns, ranging from feeble, long-lived multiple arms to strong, rapidly evolving few-armed spirals. These fluctuations induce radial migration through secular changes in the angular momentum of disk particles, mixing the disk radially and blurring pre-existing gradients. Migration primarily affects stars with small vertical excursions, regardless of spiral pattern. This “provenance bias” largely determines the vertical structure of migrating stars: inward migrators thin down as they move in, whereas outward migrators do not thicken up but rather preserve the disk scale height at their destination. Migrators of equal birth radius thus develop a strong scale-height gradient, not by flaring out as commonly assumed, but by thinning down as they spread inward. Similar gradients have been observed for low-[α/Fe] mono-abundance populations (MAPs) in the Galaxy, but our results argue against interpreting them as a consequence of radial migration. This is because outward migration does not lead to thickening, implying that the maximum scale height of any population should reflect its value at birth. In contrast, Galactic MAPs have scale heights that increase monotonically outward, reaching values that greatly exceed those at their presumed birth radii. Given the strong vertical bias affecting migration, a proper assessment of the importance of radial migration in the Galaxy should take carefully into account the strong radial dependence of the scale heights of the various stellar populations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".