Exploring the diversity of double-detonation explosions for Type Ia supernovae: effects of the post-explosion helium shell composition
Bibliographic record
Abstract
ABSTRACT The detonation of a helium shell on top of a carbon–oxygen white dwarf has been argued as a potential explosion mechanism for Type Ia supernovae (SNe Ia). The ash produced during helium shell burning can lead to light curves and spectra that are inconsistent with normal SNe Ia, but may be viable for some objects showing a light-curve bump within the days following explosion. We present a series of radiative transfer models designed to mimic predictions from double-detonation explosion models. We consider a range of core and shell masses, and systematically explore multiple post-explosion compositions for the helium shell. We find that a variety of luminosities and time-scales for early light-curve bumps result from those models with shells containing 56Ni, 52Fe, or 48Cr. Comparing our models to SNe Ia with light-curve bumps, we find that these models can reproduce the shapes of almost all of the bumps observed, but only those objects with red colours around maximum light (B − V ≳ 1) are well matched throughout their evolution. Consistent with previous works, we also show that those models in which the shell does not contain iron-group elements provide good agreement with normal SNe Ia of different luminosities from shortly after explosion up to maximum light. While our models do not amount to positive evidence in favour of the double-detonation scenario, we show that provided the helium shell ash does not contain iron-group elements, it may be viable for a wide range of normal SNe Ia.
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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 | 0.001 | 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 | 0.000 |
| 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".