Core-collapse supernovae in binaries as the origin of galactic hyper-runaway stars
Bibliographic record
Abstract
ABSTRACT Several stars detected moving at velocities near to or exceeding the Galactic escape speed likely originated in the Milky Way disc. We quantitatively explore the ‘binary supernova scenario’ hypothesis, wherein these ‘hyper-runaway’ stars are ejected at large peculiar velocities when their close, massive binary companions undergo a core-collapse supernova and the binary is disrupted. We perform an extensive suite of binary population synthesis simulations evolving massive systems to determine the assumptions and parameters that most impact the ejection rate of fast stars. In a simulation tailored to eject fast stars, we find the most likely hyper-runaway star progenitor binary is composed of a massive (${\sim}30\, \mathrm{ M}_{\odot }$) primary and an ${\sim}3\!-\!4\, \mathrm{ M}_{\odot }$ companion on an orbital period that shrinks to ≲1 d prior to the core collapse following a common-envelope phase. The black hole remnant formed from the primary must receive a natal kick ≳1000 km s−1 to disrupt the binary and eject the companion at a large velocity. We compare the fast stars produced in these simulations to a contemporary census of early-type Milky Way hyper-runaway star candidates. We find that these rare objects may be produced in sufficient number only when poorly constrained binary evolution parameters related to the strength of post-core-collapse remnant natal kicks and common-envelope efficiency are adjusted to values currently unsupported – but not excluded – by the literature. We discuss observational implications that may constrain the existence of these putative progenitor systems.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".