First asteroseismic analysis of the globular cluster M80: multiple populations and stellar mass-loss
Bibliographic record
Abstract
ABSTRACT Asteroseismology provides a new avenue for accurately measuring the masses of evolved globular cluster (GC) stars. We present the first detections of solar-like oscillations in 47 red giant branch (RGB) and early asymptotic giant branch (EAGB) stars in the metal-poor GC M80; only the second with measured seismic masses. We investigate two areas of stellar evolution and GC science: multiple populations and stellar mass-loss. We detect a distinct bimodality in the EAGB mass distribution. We suggest that this could be due to sub-population membership. If confirmed in future work with spectroscopy, it would be the first direct measurement of a mass difference between sub-populations. A mass difference was not detected between the sub-populations in our RGB sample. We instead measured an average RGB mass of $0.782\pm 0.009~\mathrm{M}_{\odot }$, which we interpret as the average of the sub-populations. Differing mass-loss rates on the RGB have been proposed as the second parameter that could explain the horizontal branch morphology variations between GCs. We calculated an integrated RGB mass-loss separately for each sub-population: $0.12\pm 0.02~\mathrm{M}_{\odot }$ (SP1) and $0.25\pm 0.02~\mathrm{M}_{\odot }$ (SP2). Thus, SP2 stars appear to have enhanced mass-loss on the RGB. Mass-loss is thought to scale with metallicity, which we confirm by comparing our results to a higher metallicity GC, M4. Finally, our study shows the robustness of the Δν-independent mass scaling relation in the low-metallicity (and low surface gravity) regime.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".