Type II-P supernova progenitor star initial masses and SN 2020jfo: direct detection, light-curve properties, nebular spectroscopy, and local environment
Bibliographic record
Abstract
ABSTRACT We present optical, ultraviolet, and infrared data of the type II supernova (SN II) 2020jfo at 14.5 Mpc. This wealth of multiwavelength data allows us to compare different metrics commonly used to estimate progenitor masses of SN II for the same object. Using its early light curve, we infer SN 2020jfo had a progenitor radius of ≈700 R⊙, consistent with red supergiants of initial mass MZAMS =11–13 M⊙. The decline in its late-time light curve is best fit by a 56Ni mass of 0.018 ± 0.007 M⊙ consistent with that ejected from SN II-P with ≈13 M⊙ initial mass stars. Early spectra and photometry do not exhibit signs of interaction with circumstellar matter, implying that SN 2020jfo experienced weak mass-loss within the final years prior to explosion. Our spectra at >250 d are best fit by models from 12 M⊙ initial mass stars. We analysed integral field unit spectroscopy of the stellar population near SN 2020jfo, finding its massive star population had a zero age main sequence mass of 9.7$\substack{+2.5\\ -1.3}~{\rm M}_{\odot }$. We identify a single counterpart in pre-explosion imaging and find it has an initial mass of at most $7.2\substack{+1.2\\ -0.6}~{\rm M}_{\odot }$. We conclude that the inconsistency between this mass and indirect mass indicators from SN 2020jfo itself is most likely caused by extinction with AV = 2–3 mag due to matter around the progenitor star, which lowered its observed optical luminosity. As SN 2020jfo did not exhibit extinction at this level or evidence for interaction with circumstellar matter between 1.6 and 450 d from explosion, we conclude that this material was likely confined within ≈3000 R⊙ from the progenitor star.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".