Comparison of Ne-22 core and shell distilled WD detonations in <scp>arepo</scp>
Bibliographic record
Abstract
ABSTRACT We present three-dimensional hydrodynamical simulations of detonations in 1.0 $\mathrm{M_{\odot }}$ white dwarfs (WDs) that have undergone $^{22} \mathrm{Ne}$ distillation during crystallization. These simulations, conducted with the moving-mesh code arepo, aim to investigate the effects of chemical separation on the ejecta and spectra of such WDs undergoing thermonuclear explosions. The distillation process alters the internal chemical stratification of the star, concentrating neutron-rich material either in a central core or in an interior shell. We model both configurations as well as a homogeneous equivalent for each case with the same $^{22} \mathrm{Ne}$ content distributed evenly at all radii. Despite similar $^{56} \mathrm{Ni}$ yields between the core and shell models (0.40 and 0.45 $\mathrm{M_{\odot }}$, respectively), the two models yield markedly different iron-group abundances. Both distilled models showed significantly enhanced production of $^{15} \mathrm{N}$ via the decay of $^{15} \mathrm{O}$. The $^{22} \mathrm{Ne}$-core model produces enhanced amounts of stable neutron-rich iron-group isotopes such as $^{58} \mathrm{Ni}$ and $^{54} \mathrm{Fe}$. We highlight observational signatures associated with these differences, including potentially enhanced [Ni ii] lines in nebular spectra. Synthetic tardis spectra at early times show only moderate differences. Our results suggest that WD distillation, a process linked to delayed cooling in the Gaia Q branch population, may leave detectable nucleosynthetic fingerprints in a subset of Type Ia supernovae. These findings open additional pathways to probe progenitor evolution and the role of crystallization in shaping the diversity of thermonuclear transients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".