Binaries in the formation of multiple populations
Bibliographic record
Abstract
Globular clusters are not simple stellar populations. Practically all globular clusters show multiple populations (MPs), where at the same metallicity [Fe/H], approximately half of their stars are enriched by the products of high-temperature hydrogen burning relative to the rest that show field-like abundances. The source of enrichment for forming the enriched population is an unresolved problem. Interacting massive binaries are an underexplored proposed source of enrichment. Many assessments of the theory are based on only one modelled binary. We simulate a suite of metal-intermediate, [Fe/H]=-1.44, interacting binaries with initial primary masses of 10 to 40 solar masses, with mass ratios ranging from 0.15 to 0.9, over periods ranging from about 2 to 700 days using MESA. Our simulations show that binaries at higher masses, higher mass ratios, and near our upper period limit tend to be the most enriching with ejecta showing HeNaCNOAlMg variations consistent with hot-H burning. Some binaries do not eject material, suggesting binary mass loss can contribute to the dilution of enrichment. As a realistic population, binaries within our parameter space eject about ten times as much mass as they would as single stars. Ejection occurs on timescales of about 11 Myr, consistent with observed and theoretical limits on the age spreads for MPs. Our systems are rare, making them more suited to explaining the stochastic nature of MPs but not the large fraction of enriched stars. Spreads in He, N, Na, C, and Al for our ejecta could reasonably explain the observed spreads in clusters. Reduced variation in O and Mg suggests more massive binaries should be investigated. A multi-scale approach to cluster formation with multiple types of enrichment sources is a necessary next step for validating MP formation scenarios.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".