PhysicsarXiv
Heuristic editor, no API keyVerdict: NotableGravitational Waves from Core-Collapse Supernovae: Dependence on the Progenitor Star, Rotation Rate and Nuclear Equation of State
We simulate 137 axisymmetric core-collapse supernova explosions to systematically investigate the impact of different progenitor properties, rotation rates, and equations of state on the supernova gravitational-wave…
Key numbers
- 62 % for models close to
VerdictWorth a reader's time today.
Abstract
We simulate 137 axisymmetric core-collapse supernova explosions to systematically investigate the impact of different progenitor properties, rotation rates, and equations of state on the supernova gravitational-wave emission. We use 15 different progenitor stars, with masses ranging from 9.71 M_odot to 36.61 M_odot, three equations of state, and three rotation rates, with durations extending up to 5.5\,s after bounce. We find substantial differences in the gravitational-wave emission between equations of state, with the CMF equation of state producing lower gravitational-wave amplitudes and a longer low frequency mode due to the standing accretion shock instability that remains visible even at ~5\,s post bounce. Rapid rotation also significantly alters the gravitational-wave signal, with more visible modes in the gravitational-wave emission, and lower energies due to later shock revival times. We include the gravitational-wave emission due to neutrino memory, and show it can significantly improve the detectability of core-collapse supernovae for observatories with improved low frequency sensitivity. We propose a recalibration of universal relations for the high frequency mode, using fits to our waveforms, that reduces the fit error at late times in the gravitational-wave signal. Finally, we investigate, for the first time, the impact of random seed perturbations on the gravitational-wave emission. We find that stochastic perturbations can produce dramatic variations in gravitational-wave amplitude, and can alter the signal-to-noise ratio of a detection by as much as 62% for models close to the boundary between failed and successful shock revival.
The editor's rubric
| Dimension | Level | Weight | What that level means |
|---|---|---|---|
| Leverage | ███░░ 3 | 18% | A method or resource many groups across the field will adopt within a year. |
| Magnitude | ███░░ 3 | 20% | Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem. |
| Evidence | ███░░ 3 | 22% | Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data. |
| Novelty | ███░░ 3 | 22% | A genuinely new approach to an open problem. |
| Trajectory | ██░░░ 2 | 10% | Some room to improve with obvious engineering. |
| Stakes | ██░░░ 2 | 8% | Benefits a professional community (practitioners, clinicians, engineers). |
Editor’s rationale
Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: method (we propose, we report); breadth (general-purpose); firsts (for the first time, first); verification (false alarm rate); stakes (climate).
How the score was computed
- Merit
- 5.6 / 10
- Adjusted merit
- 4.7 / 10
- Attention
- 0%
- Freshness
- 80%
- Citations0 (reference 20, via semantic-scholar, Sep 29, 2026, 23:37 UTC)