Constraints on the Distance Moduli, Helium, and Metal Abundances, and Ages of Globular Clusters from Their RR Lyrae and Non-variable Horizontal Branch Stars. II. Multiple Stellar Populations in 47 Tuc, M3, and M13
Bibliographic record
Abstract
Abstract We present a new set of horizontal branch (HB) models computed with the MESA stellar evolution code. The models adopt α-enhanced Asplund et al. metal mixtures and include the gravitational settling of He. They are used in our HB population synthesis tool to generate theoretical distributions of HB stars in order to describe the multiple stellar populations in the globular clusters 47 Tuc, M3, and M13. The observed HB in 47 Tuc is reproduced very well by our simulations for and if the initial helium mass fraction varies by , and approximately 21%, 37%, and 42% of the stars have , 0.270, and 0.287, respectively. These simulations yield , implying an age near 13.0 Gyr. In the case of M3 and M13, our synthetic HBs for and match the observed ones quite well if M3 has and , resulting in an age of 12.6 Gyr, whereas M13 has and , implying an age of 12.9 Gyr. Mass loss during giant branch evolution and appear to be the primary second parameters for M3 and M13. New observations for seven of the nine known RR Lyrae in M13 are also reported. Surprisingly, periods predicted for the c-type variables tend to be too high (by up to ∼0.1 days).
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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 | 0.002 |
| 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 | 0.000 |
| 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".