i-process Contribution of Rapidly Accreting White Dwarfs to the Solar Composition of First-peak Neutron-capture Elements
Bibliographic record
Abstract
Abstract Rapidly accreting white dwarfs (RAWDs) have been proposed as contributors to the chemical evolution of heavy elements in the Galaxy. Here, we test this scenario for the first time and determine the contribution of RAWDs to the solar composition of first-peak neutron-capture elements. We add the metallicity-dependent contribution of RAWDs to the one-zone galactic chemical evolution code OMEGA according to RAWD rates from binary stellar population models combined with metallicity-dependent i-process stellar yields calculated following the models of Denissenkov et al. With this approach, we find that the contribution of RAWDs to the evolution of heavy elements in the Galaxy could be responsible for a significant fraction of the solar composition of Kr, Rb, Sr, Y, Zr, Nb, and Mo ranging from 2% to 45% depending on the element, the enrichment history of the Galactic gas, and the total mass ejected per RAWD. This contribution could explain the missing solar Lighter Element Primary Process for some elements (e.g., Sr, Y, and Zr). We do not overproduce any isotope relative to the solar composition, but 96Zr is produced in a similar amount. The i process produces efficiently the Mo stable isotopes 95Mo and 97Mo. When nuclear reaction rate uncertainties are combined with our GCE uncertainties, the upper limits for the predicted RAWD contribution increase by a factor of 1.5–2 for Rb, Sr, Y, and Zr, and by 3.8 and 2.4 for Nb and Mo, respectively. We discuss the implication of the RAWD stellar evolution properties on the single-degenerate SN Ia scenario.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".