Determining the <sup>56</sup>Ni distribution of type Ia supernovae from observations within days of explosion
Bibliographic record
Abstract
Recent studies have shown how the distribution of 56Ni within the ejected material of type Ia supernovae can have profound consequences on the observed light curves. Observations at early times can therefore provide important details on the explosion physics in thermonuclear supernovae, which are poorly constrained. To this end, we present a series of radiative transfer calculations that explore variations in the 56Ni distribution. Our models also show the importance of the density profile in shaping the light curve, which is often neglected in the literature. Using our model set, we investigate the observations that are necessary to determine the 56Ni distribution as robustly as possible within the current model set. We find that this includes observations beginning at least ∼14 days before B-band maximum, extending to approximately maximum light with a relatively high (≲3 day) cadence, and in at least one blue and one red band (such as B and R, or g and r) are required. We compare a number of well-observed type Ia supernovae that meet these criteria to our models and find that the light curves of ∼70–80% of objects in our sample are consistent with being produced solely by variations in the 56Ni distributions. The remaining supernovae show an excess of flux at early times, indicating missing physics that is not accounted for within our model set, such as an interaction or the presence of short-lived radioactive isotopes. Comparing our model light curves and spectra to observations and delayed detonation models demonstrates that while a somewhat extended 56Ni distribution is necessary to reproduce the observed light curve shape, this does not negatively affect the spectra at maximum light. Investigating current explosion models shows that observations typically require a shallower decrease in the 56Ni mass towards the outer ejecta than is produced for models of a given 56Ni mass. Future models that test differences in the explosion physics and detonation criteria should be explored to determine the conditions necessary to reproduce the 56Ni distributions found here.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".