Trans-Fe elements from type Ia supernovae
Bibliographic record
Abstract
Context. A type Ia supernova (SNIa) marks the catastrophic explosion of a white dwarf in a binary system. These events play a crucial role in galactic chemical evolution and serve as pivotal standardisable candles for measuring cosmic distances, underpinning the discovery of the Universe’s accelerated expansion. However, the progenitors of SNIa remain uncertain, introducing challenges to their use in cosmology and nucleosynthesis predictions. Aims. In this work, we present a grid of five models detailing the evolution and nucleosynthesis of slowly merging carbon-oxygen white dwarfs approaching the Chandrasekhar mass. Methods. These models test a variety of physics input settings, including accretion rates, nuclear reaction rates, convection parameters, and the composition of the accreted material. During the merger process, as the mass of the primary white dwarf approaches the Chandrasekhar limit, carbon burning is initiated first on the surface before eventually igniting explosively at the centre. As a consequence, the 22 Ne( α , n ) 25 Mg reaction activates in the outer layers of all models. Results. The neutrons released in this way produce a weak s -process-like abundance distribution peaking at Kr, which is overproduced by more than a factor of ∼1000 compared to solar. The trans-Fe elements-enriched outer layer mass varies from ∼0.04 M ⊙ to ∼0.11 M ⊙ , depending on the accretion rate. Our explosion simulation of these progenitor models ejects a significant amount of first-peak elements (e.g. Kr, Sr) as well as some long-lived radioactive species, such as 60 Fe. Conclusions. In a previous theoretical study, we found that a similar nucleosynthesis process during the progenitor phase may also occur on the surface of near-Chandrasekhar white dwarfs formed through the accretion of H-rich material via the single-degenerate scenario. Therefore, these results suggest that trans-Fe enrichment might be a hallmark of near-Chandrasekhar SNIa ejecta, regardless of the specific progenitor channel, and could provide a new spectral signature that distinguishes them from sub-Chandrasekhar explosions.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.004 | 0.001 |
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".