SN 2020wnt: a slow-evolving carbon-rich superluminous supernova with no O <scp>ii</scp> lines and a bumpy light curve
Bibliographic record
Abstract
ABSTRACT We present the analysis of SN 2020wnt, an unusual hydrogen-poor superluminous supernova (SLSN-I), at a redshift of 0.032. The light curves of SN 2020wnt are characterized by an early bump lasting ∼5 d, followed by a bright main peak. The SN reaches a peak absolute magnitude of M$_{r}^{\rm max}=-20.52\pm 0.03$ mag at ∼77.5 d from explosion. This magnitude is at the lower end of the luminosity distribution of SLSNe-I, but the rise-time is one of the longest reported to date. Unlike other SLSNe-I, the spectra of SN 2020wnt do not show O ii, but strong lines of C ii and Si ii are detected. Spectroscopically, SN 2020wnt resembles the Type Ic SN 2007gr, but its evolution is significantly slower. Comparing the bolometric light curve to hydrodynamical models, we find that SN 2020wnt luminosity can be explained by radioactive powering. The progenitor of SN 2020wnt is likely a massive and extended star with a pre-SN mass of 80 M⊙ and a pre-SN radius of 15 R⊙ that experiences a very energetic explosion of 45 × 1051 erg, producing 4 M⊙ of 56Ni. In this framework, the first peak results from a post-shock cooling phase for an extended progenitor, and the luminous main peak is due to a large nickel production. These characteristics are compatible with the pair-instability SN scenario. We note, however, that a significant contribution of interaction with circumstellar material cannot be ruled out.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".