Related papers: Phenomenological gravitational waveforms for core-…
Detecting unmodeled gravitational wave (GW) bursts presents significant challenges due to the lack of accurate waveform templates required for matched-filtering techniques. A primary difficulty lies in distinguishing genuine signals from…
Magnetized and rotating core-collapse supernovae (CCSNe) are promising candidates for producing long gamma-ray bursts and hypernovae. In this project, we present 34 two-dimensional magnetized core-collapse supernova simulations with…
Core-collapse supernovae (SNe) are sources of gravitational waves (GWs) produced by hydrodynamical instabilities and highly time-dependent anisotropies of the neutrino radiation. In this work we analyze both contributions to the GW signal…
The core collapse of a massive star at the end of its life can give rise to one of the most powerful phenomena in the Universe. Because of violent mass motions that take place during the explosion, core-collapse supernovae have been…
Core-collapse supernovae are predicted to produce gravitational waves (GWs) that may be detectable by Advanced LIGO/Virgo. These GW signals carry information from the heart of these catacylsmic events, where matter reaches nuclear…
We present a new theory for the gravitational wave signatures of core-collapse supernovae. Previous studies identified axisymmetric rotating core collapse, core bounce, postbounce convection, and anisotropic neutrino emission as the primary…
Core-collapse supernovae (CCSNe) are potential multimessenger events detectable by current and future gravitational wave (GW) detectors. The GW signals emitted during these events are expected to provide insights into the explosion…
Using predictions from three-dimensional (3D) hydrodynamics simulations of core-collapse supernovae (CCSNe), we present a coherent network analysis to detection, reconstruction, and the source localization of the gravitational-wave (GW)…
Recent core-collapse supernova (CCSN) simulations have predicted several distinct features in gravitational-wave (GW) spectrograms, including a ramp-up signature due to the g-mode oscillation of the proto-neutron star (PNS) and an excess in…
Core-collapse supernovae (CCSN) are a prime source of gravitational waves. Estimations of their typical frequencies make them perfect targets for the current network of advanced, ground-based detectors. A successful detection could…
Gravitational waves from core-collapse supernovae are produced by the excitation of different oscillation modes in the proto-neutron star (PNS) and its surroundings, including the shock. In this work we study the relationship between the…
We study gravitational waves (GWs) from a set of two-dimensional multi-group neutrino radiation hydrodynamic simulations of core-collapse supernovae (CCSNe). Our goal is to systematize the current knowledge about the post-bounce CCSN GW…
Galactic core-collapse supernovae are among the possible sources of gravitational waves. We investigate the ability of gravitational-wave observatories to extract the properties of the collapsing progenitor from the gravitational waves…
The next galactic core-collapse supernova (CCSN) has already exploded, and its electromagnetic (EM) waves, neutrinos, and gravitational waves (GWs) may arrive at any moment. We present an extensive study on the potential sensitivity of…
We present self-consistent three-dimensional core-collapse supernova simulations of a rotating $20M_\odot$ progenitor model with various initial angular velocities from $0.0$ to $4.0$ rad s$^{-1}$ using a smoothed particle hydrodynamics…
Core-collapse supernovae (CCSNe) offer extremely valuable insights into the dynamics of galaxies. Neutrino time profiles from CCSNe, in particular, could reveal unique details about collapsing stars and particle behavior in dense…
Using the latest numerical simulations of rotating stellar core collapse, we present a Bayesian framework to extract the physical information encoded in noisy gravitational wave signals. We fit Bayesian principal component regression models…
We demonstrate the application of a convolutional neural network to the gravitational wave signals from core collapse supernovae. Using simulated time series of gravitational wave detectors, we show that based on the explosion mechanisms, a…
We test deep-learning (DL) techniques for the analysis of rotational core-collapse supernovae (CCSN) gravitational-wave (GW) signals by performing classification and parameter inference of the maximum (peak) frequency and the GW strain…
We present an analysis of gravitational wave (GW) predictions from five two-dimensional Core Collapse Supernova (CCSN) simulations that varied only in the Equation of State (EOS) implemented. The GW signals from these simulations are used…