The very young resolved stellar populations around stripped-envelope supernovae
Bibliographic record
Abstract
The massive star origins for Type IIP supernovae (SNe) have been established through direct detection of their red supergiants progenitors in pre-explosion observations; however, there has been limited success in the detection of the progenitors of H-deficient SNe. The final fate of more massive stars, capable of undergoing a Wolf-Rayet phase, and the origins of Type Ibc SNe remains debated, including the relative importance of single massive star progenitors or lower mass stars stripped in binaries. We present an analysis of the ages and spatial distributions of massive stars around the sites of 23 stripped-envelope SNe, as observed with the Hubble Space Telescope, to probe the possible origins of the progenitors of these events. Using a Bayesian stellar populations analysis scheme, we find characteristic ages for the populations observed within $150\,\mathrm{pc}$ of the target Type IIb, Ib and Ic SNe to be $\log (t) = 7.20$, $7.05$ and $6.57$, respectively. The Type Ic SNe in the sample are nearly all observed within $100\,\mathrm{pc}$ of young, dense stellar populations. The environment around SN 2002ap is an important exception both in terms of age and spatial properties. These findings may support the hypothesis that stars with $M_{init} > 30M_{\odot}$ produce a relatively large proportion of Type Ibc SNe, and that these SN subtypes arise from progressively more massive progenitors. Significantly higher extinctions are derived towards the populations hosting these SNe than previously used in analysis of constraints from pre-explosion observations. The large initial masses inferred for the progenitors are in stark contrast with the low ejecta masses estimated from SN light curves.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".