The demographics of binary companions to stripped-envelope supernovae: confronting population synthesis models with observations
Bibliographic record
Abstract
ABSTRACT Stripped-envelope supernovae (SESNe) mark the deaths of massive stars without hydrogen-rich envelopes. Most SESNe likely originate from binary systems where a companion stripped the progenitor of its envelope. Years of HST imaging of nearby SESN sites have produced a statistically meaningful sample of constraints on surviving binary companions. We assemble the current sample of six companion detections and six non-detections from the literature, re-analysing whenever needed. We then conduct the first statistical comparison with binary population-synthesis predictions, primarily based on new calculations performed with the POSYDON framework. Across a metallicity range, our models predict that 80–90 % of Type Ib/c and 60–85 % of IIb SNe explode with a rapidly rotating main-sequence companion. The observed luminosity distribution favours fairly inefficient mass accretion and failed explosions of the most massive stripped stars. The companion detection fraction broadly matches predictions, given the imaging depth, but appears elevated for SN IIb. In all but one non-detection, a faint undetected companion is the most likely scenario. The red apparently evolved companions in a few SN Ib/c may result from strong interaction with the ejecta, expected in $\sim 12~\%$ of them. Companion demographics offer a powerful independent probe of SESN progenitor systems, with the current sample disfavouring efficient accretion and supporting Wolf–Rayet non-explodability. Larger companion samples and follow-up studies will further clarify binary pathways to SESNe, serving as benchmarks for transient surveys.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".