Serendipitous detection of the dusty Type IIL SN 1980K with <i>JWST</i>/MIRI
Bibliographic record
Abstract
ABSTRACT We present mid-infrared (mid-IR) imaging of the Type IIL supernova (SN) 1980K with the JWST more than 40 yr post-explosion. SN 1980K, located in the nearby (D ≈ 7 Mpc) ‘SN factory’ galaxy NGC 6946, was serendipitously captured in JWST/MIRI images taken of the field of SN 2004et in the same galaxy. SN 1980K serves as a promising candidate for studying the transitional phase between young SNe and older SN remnants and also provides a great opportunity to investigate its the close environment. SN 1980K can be identified as a clear and bright point source in all eight MIRI filters from F560W up to F2550W. We fit analytical dust models to the mid-IR spectral energy distribution that reveal a large amount (Md ≈ 0.002 M⊙) of Si-dominated dust at $T_\rm {dust}\approx 150$ K (accompanied by a hotter dust/gas component), and also computed numerical SED dust models. Radiative transfer modelling of a late-time optical spectrum obtained recently with Keck discloses that an even larger (∼0.24–0.58 M⊙) amount of dust is needed in order for selective extinction to explain the asymmetric line profile shapes observed in SN 1980K. As a conclusion, with JWST, we may see i) pre-existing circumstellar dust heated collisionally (or, partly radiatively), analogous to the equatorial ring of SN 1987A, or ii) the mid-IR component of the presumed newly-formed dust, accompanied by much more colder dust present in the ejecta (as suggested by the late-time the optical spectra).
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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 | 0.000 |
| 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".