Machine learning extracts core rotation and signal properties from CCSN gravitational waves, with next-generation detectors constraining rotation beyond 100 kpc for favorable orientations despite some uncertainties.
Gravitational waves from 3D MHD core collapse simulations
2 Pith papers cite this work. Polarity classification is still indexing.
abstract
We present the gravitational wave analysis from rotating (model s15g) and nearly non-rotating (model s15h) 3D MHD core collapse supernova simulations at bounce and the first couple of ten milliseconds afterwards. The simulations are launched from 15M_{\odot} progenitor models stemming from stellar evolution calculations. Gravity is implemented by a spherically symmetric effective general relativistic potential. The input physics uses the Lattimer-Swesty equation of state for hot, dense matter and a neutrino parametrisation scheme that is accurate until the first few ms after bounce. The 3D simulations allow us to study features already known from 2D simulations as well as nonaxisymmetric effects. In agreement with recent results we find only type I gravitational wave signals at core bounce. In the later stage of the simulations, one of our models (s15g) shows nonaxisymmetric gravitational wave emission caused by a low T/|W| dynamical instability, while the other model radiates gravitational waves due to a convective instability in the protoneutron star. The total energy released in gravitational waves within the considered time intervals is 1.52\times10^{-7}M_{\odot} (s15g) and 4.72\times10^{-10}M_{\odot} (s15h). Both core collapse simulations indicate that corresponding events in our Galaxy would be detectable either by the LIGO or Advanced LIGO detector.
citation-role summary
citation-polarity summary
fields
astro-ph.HE 2years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
Simulations show the low-T/|W| instability develops robustly across five nuclear EOS in a rapidly rotating 35 M⊙ progenitor, with dominant GW frequency correlating to PNS compactness and stiffness.
citing papers explorer
-
Parameter Estimation Horizon of Core-Collapse Supernovae with Current and Next-Generation Gravitational-Wave Detectors
Machine learning extracts core rotation and signal properties from CCSN gravitational waves, with next-generation detectors constraining rotation beyond 100 kpc for favorable orientations despite some uncertainties.
-
Impact of the equation of state on core collapse supernovae I: the low-$T/|W|$ instability
Simulations show the low-T/|W| instability develops robustly across five nuclear EOS in a rapidly rotating 35 M⊙ progenitor, with dominant GW frequency correlating to PNS compactness and stiffness.