230 citations · 802 across the 18 of their papers we have counts for
4 papers · 1 filter
Bayesian inference from gravitational waves in fast-rotating, core-collapse supernovae
Carlos Pastor-Marcos, Pablo Cerdá-Durán, Daniel Walker +4
Core-collapse supernovae (CCSNe) are prime candidates for gravitational-wave detectors. The analysis of their complex waveforms can potentially provide information on the physical…
Comparison of neural network architectures for feature extraction from binary black hole merger waveforms
Osvaldo Gramaxo Freitas, Juan Calderón Bustillo, José A. Font +3
We evaluate several neural-network architectures, both convolutional and recurrent, for gravitational-wave time-series feature extraction by performing point parameter estimation o…
Gradient-Annihilated PINNs for Solving Riemann Problems: Application to Relativistic Hydrodynamics
Antonio Ferrer-Sánchez, José D. Martín-Guerrero, Roberto Ruiz de Austri +2
We present a novel methodology based on Physics-Informed Neural Networks (PINNs) for solving systems of partial differential equations admitting discontinuous solutions. Our method…
Multi-messenger observations of core-collapse supernovae: Exploiting the standing accretion shock instability
Marco Drago, Haakon Andresen, Irene Di Palma +2
The gravitational wave (GW) and neutrino signals from core-collapse supernovae (CCSNe) are expected to carry pronounced imprints of the standing accretion shock instability (SASI).…