Stellar Modeling for Nuclear Astrophysics: Constraining the astrophysical origin of the p-nuclei
Bibliographic record
Abstract
The production of the p-process nuclides that we observe today in the Solar Systemis still uncertain. Recent Galactic Chemical Evolution (GCE) calculations, showedthat explaining the inventory of the p-nuclides by the contribution from Core col-lapse supernovae (ccSNe) alone is challenging, thus requiring a complementary con-tribution from thermonuclear supernovae (SNe Ia), assuming in this last case ans-process rich pre-explosive seeds distribution, built byneutron captures during theaccretion phase. Presently there are no complete stellar models calculating theseabundances. We calculate accreting white dwarfs (WDs) models with five differentinitial masses using the stellar code MESA. We then focus on the nucleosynthesiscalculating the full abundance distribution. In these models the dominant neutronsource are22Ne(α,n)25Mg, activated at the bottom of the convective thermal pulsedriven by the Helium flashes along the accretion phase, for WDmasses lower than1.26 M⊙, and13C(α,n)16O for WD masses equal or higher than 1.26 M⊙. We foundneutron densities up to few 1015cm−3in the most massive WDs. In particular, weobtain a strong production by neutron captures up to the Pb region, showing howthe classic assumption of a neutron-capture rich pre-explosive seeds distribution isjustified. Using these results, we compute the resulting explosive nucleosynthesis ofproton rich heavy stable isotopes using a multi-D SNe Ia model, and discuss the un-certainties affecting our results, focusing in particular on the nuclear reaction-rateswhich provide the dominant contribution to the production uncertainty, highlightingwhich of the identified key reactions are realistic candidates for future experiments.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".