Deciphering the Milky Way’s star formation at cosmic noon with high proper-motion stars
Bibliographic record
Abstract
Context. Evidence suggests that the Milky Way (MW) underwent a major collision with the Gaia–Sausage/Enceladus (GSE) dwarf galaxy around cosmic noon. While GSE has since been fully disrupted, it brought in ex situ stars and dynamically heated in situ stars into the halo. In addition, the gas-rich merger may have triggered a burst of in situ star formation, potentially giving rise to a chemically distinct stellar component. Aims. We investigated the region of phase space where stars formed during the GSE merger likely reside, and retain distinct chemical and dynamical signatures. Methods. Building on our previous investigation of metallicity ([Fe/H]) and vertical angular momentum (LZ) distributions, we analysed spectroscopic samples from GALAH, APOGEE, SDSS, and LAMOST, combined with Gaia kinematics. We focused on high proper-motion stars as effective tracers of the phase-space volume likely influenced by the GSE merger. To correct for selection effects, we incorporated metallicity estimates derived from SDSS and SMSS photometry. Results. Our analysis reveals that low-α stars with GSE-like kinematics exhibit bimodality in [Na/Fe] and [Al/Fe] at −1.0 ≲[Fe/H] ≲ −0.4. One group follows the low light-element abundances of GSE stars, while another exhibits enhanced values. These low-α, high-Na stars have eccentric orbits but are more confined to the inner MW. Eos overlaps with a high-eccentricity subset of these stars, implying that it constitutes a smaller structure nested within the broader population. After correcting for sampling biases, we estimated a population ratio of approximately 1:10 between the low-α, high-Na stars and the GSE debris. Conclusions. These results suggest that the low-α, high-Na stars formed in a compact region, likely fuelled by gas from the GSE progenitor, analogous to clumpy star-forming clouds seen in high-redshift galaxies. Such stars may trace the first sparks of more extensive merger-driven starburst activity.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".