Massive stars exploding in a He-rich circumstellar medium
Bibliographic record
Abstract
We present optical and near-infrared observations of two Type Ibn supernovae (SNe), SN 2018jmt and SN 2019cj. Their light curves have rise times of about ten days, reaching an absolute peak magnitude of M g (SN 2018jmt) = −19.07 ± 0.37 and M V (SN 2019cj) = −18.94 ± 0.19 mag, respectively. The early-time spectra of SN 2018jmt are dominated by a blue continuum, accompanied by narrow (600−1000 km s −1 ) He I lines with the P-Cygni profile. At later epochs, the spectra become more similar to those of the prototypical SN Ibn 2006jc. At early phases, the spectra of SN 2019cj show flash ionisation emission lines of C III , N III , and He II superposed on a blue continuum. These features disappear after a few days, and then the spectra of SN 2019cj evolve similarly to those of SN 2018jmt. The spectra indicate that the two SNe exploded within a He-rich circumstellar medium (CSM) lost by the progenitors a short time before the explosion. We modelled the light curves of the two SNe Ibn to constrain the progenitor and the explosion parameters. The ejecta masses are consistent with either what is expected for a canonical SN Ib (∼2 M ⊙ ) or for a massive Wolf Rayet star (> ∼4 M ⊙ ), with the kinetic energy on the order of 10 51 erg. The lower limit on the ejecta mass (> ∼2 M ⊙ ) argues against a scenario involving a relatively low-mass progenitor (e.g. M ZAMS ∼ 10 M ⊙ ). We set a conservative upper limit of ∼0.1 M ⊙ for the 56 Ni masses in both SNe. From the light curve modelling, we determined a two-zone CSM distribution, with an inner, flat CSM component and an outer CSM with a steeper density profile. The physical properties of SN 2018jmt and SN 2019cj are consistent with those expected from the core collapse of relatively massive envelope-stripped stars.
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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) | 0.000 | 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".