KSP-SN-2016kf: A Long-rising H-rich Type II Supernova with Unusually High <sup>56</sup>Ni Mass Discovered in the KMTNet Supernova Program
Bibliographic record
Abstract
Abstract We present the discovery and the photometric and spectroscopic study of H-rich Type II supernova (SN) KSP-SN-2016kf (SN2017it) observed in the KMTNet Supernova Program in the outskirts of a small irregular galaxy at z ≃ 0.043 within a day of the explosion. Our high-cadence, multi-color (BVI) light curves of the SN show that it has a very long rise time (t rise ≃ 20 days in the V band), a moderately luminous peak (M V ≃ −17.6 mag), a notably luminous and flat plateau (M V ≃ −17.4 mag and decay slope s ≃ 0.53 mag per 100 days), and an exceptionally bright radioactive tail. Using the color-dependent bolometric correction to the light curves, we estimate the 56Ni mass powering the observed radioactive tail to be 0.10 ± 0.01 M ☉, making it an H-rich Type II SN with one of the largest 56Ni masses observed to date. The results of our hydrodynamic simulations of the light curves constrain the mass and radius of the progenitor at the explosion to be ∼15 M ☉ (evolved from a star with an initial mass of ∼18.8 M ☉) and ∼1040 R ☉, respectively, with the SN explosion energy of ∼1.3 × 1051 erg. The above-average mass of the KSP-SN-2016kf progenitor, together with its low metallicity of obtained from spectroscopic analysis, is indicative of a link between the explosion of high-mass red supergiants and their low-metallicity environment. The early part of the observed light curves shows the presence of excess emission above what is predicted in model calculations, suggesting there is interaction between the ejecta and circumstellar material. We further discuss the implications of the high initial mass of the progenitor and the low-metallicity environment of KSP-SN-2016kf for our understanding of the origin of Type II SNe.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".