Bibliographic record
Abstract
An excess of flux (i.e. a bump) in the early light curves of type Ia supernovae has been observed in a handful of cases. Multiple scenarios have been proposed to explain this excess flux. Recently, it has been shown that for at least one object (SN 2018oh) the excess emission observed could be the result of a large amount of 56Ni in the outer ejecta (∼0.03 M⊙). We present a series of model light curves and spectra for ejecta profiles containing 56Ni shells of varying masses (0.01, 0.02, 0.03, and 0.04 M⊙) and widths. We find that even for our lowest mass 56Ni shell, an increase of >2 magnitudes is produced in the bolometric light curve at one day after explosion relative to models without a 56Ni shell. We show that the colour evolution of models with a 56Ni shell differs significantly from those without and shows a colour inversion similar to some double-detonation explosion models. Furthermore, spectra of our 56Ni shell models show that strong suppression of flux between ∼3700–4000 Å close to maximum light appears to be a generic feature for this class of model. Comparing our models to observations of SNe 2017cbv and 2018oh, we show that a 56Ni shell of 0.02–0.04 M⊙ can match shapes of the early optical light curve bumps, but the colour and spectral evolution are in disagreement. Our models also predict a strong UV bump that is not observed. This would indicate that an alternative origin for the flux excess is necessary. In addition, based on existing explosion scenarios, producing such a 56Ni shell in the outer ejecta as required to match the light curve shape, without the presence of additional short-lived radioactive material, may prove challenging. Given that only a small amount of 56Ni in the outer ejecta is required to produce a bump in the light curve, such non-monotonically decreasing 56Ni distributions in the outer ejecta must be rare, if they were to occur at all.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".