Stellar migrations and metal flows – Chemical evolution of the thin disc of a simulated Milky Way analogous galaxy
Bibliographic record
Abstract
ABSTRACT In order to understand the roles of metal flows in galaxy formation and evolution, we analyse our self-consistent cosmological chemodynamical simulation of a Milky Way like galaxy during its thin-disc phase. Our simulated galaxy disc qualitatively reproduces the variation of the dichotomy in [α/Fe]–[Fe/H] at different Galactocentric distances as derived by APOGEE-DR16, as well as the stellar age distribution in [α/Fe]–[Fe/H] from APOKASC-2. The disc grows from the inside out, with a radial gradient in the star-formation rate during the entire phase. Despite the radial dependence, the outflow-to-infall ratio of metals in our simulated halo shows a time-independent profile scaling with the disc growth. The simulated disc undergoes two modes of gas inflow: (i) an infall of metal-poor and relatively low-[α/Fe] gas, and (ii) a radial flow where already chemically enriched gas moves inwards with an average velocity of ∼0.7 km s−1. Moreover, we find that stellar migrations mostly happen outwards, on typical time-scales of ∼5 Gyr. Our predicted radial metallicity gradients agree with the observations from APOGEE-DR16, and the main effect of stellar migrations is to flatten the radial metallicity profiles by 0.05 dex/kpc in the slopes. We also show that the effect of migrations can appear more important in [α/Fe] than in the [Fe/H]–age relation of thin-disc stars.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".