APPLICATION OF A THEORY AND SIMULATION-BASED CONVECTIVE BOUNDARY MIXING MODEL FOR AGB STAR EVOLUTION AND NUCLEOSYNTHESIS
Bibliographic record
Abstract
ABSTRACT The s -process nucleosynthesis in Asymptotic giant branch (AGB) stars depends on the modeling of convective boundaries. We present models and s -process simulations that adopt a treatment of convective boundaries based on the results of hydrodynamic simulations and on the theory of mixing due to gravity waves in the vicinity of convective boundaries. Hydrodynamics simulations suggest the presence of convective boundary mixing (CBM) at the bottom of the thermal pulse-driven convective zone. Similarly, convection-induced mixing processes are proposed for the mixing below the convective envelope during third dredge-up (TDU), where the pocket for the s process in AGB stars forms. In this work, we apply a CBM model motivated by simulations and theory to models with initial mass M = 2 and , and with initial metal content Z = 0.01 and Z = 0.02. As reported previously, the He-intershell abundances of and are increased by CBM at the bottom of the pulse-driven convection zone. This mixing is affecting the ( α , n) activation and the s -process efficiency in the -pocket. In our model, CBM at the bottom of the convective envelope during the TDU represents gravity wave mixing. Furthermore, we take into account the fact that hydrodynamic simulations indicate a declining mixing efficiency that is already about a pressure scale height from the convective boundaries, compared to mixing-length theory. We obtain the formation of the -pocket with a mass of . The final s -process abundances are characterized by and the heavy-to-light s -process ratio is . Finally, we compare our results with stellar observations, presolar grain measurements and previous work.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".