Related papers: Classification of the core-collapse supernova expl…

A new class of core-collapse supernovae (SNe) has been discovered in recent years by optical/infrared surveys; these SNe suggest the presence of one or more extremely dense (~10^5-10^11 cm^-3) shells of circumstellar material (CSM) on…

The details of the physical mechanism that drives core-collapse supernovae (CCSNe) remain uncertain. While there is an emerging consensus on the qualitative outcome of detailed CCSN mechanism simulations in 2D, only recently have…

Core-collapse supernovae are the endproducts of massive stars, and yield radio events whose brightness depends on the intensity of the interaction experienced by the supernova ejecta with the circumstellar presupernova wind material. The…

In this study, we employ a convolutional neural network to classify gravitational waves originating from core-collapse supernovae. Training is conducted using spectrograms derived from three-dimensional numerical simulations of waveforms,…

In this work we report briefly on the gravitational wave (GW) signal computed in the context of a self-consistent, 3D simulation of a core-collapse supernova (CCSN) explosion of a 15M$_\odot$ progenitor star. We present a short overview of…

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…

Core-collapse supernovae are among the most energetic cosmic cataclysms. They are prodigious emitters of neutrinos and quite likely strong galactic sources of gravitational waves. Observation of both neutrinos and gravitational waves from…

We optimize the third-generation gravitational-wave detector to maximize the range to detect core-collapse supernovae. Based on three-dimensional simulations for core-collapse and the corresponding gravitational-wave waveform emitted, the…

Gravitational waves from core-collapse supernovae offer a unique probe of the equation of state (EOS) of dense nuclear matter. For rapidly rotating stars, previous machine-learning studies demonstrated promising EOS classification accuracy.…

We discuss the science motivations and prospects for a joint analysis of gravitational-wave (GW) and low-energy neutrino data to search for prompt signals from nearby supernovae (SNe). Both gravitational-wave and low-energy neutrinos are…

We present a detailed theoretical analysis of the gravitational-wave (GW) signal of the post-bounce evolution of core-collapse supernovae (SNe), employing for the first time relativistic, two-dimensional (2D) explosion models with…

I estimate the frequencies of gravitational waves from jittering jets that explode core collapse supernovae (CCSNe) to crudely be 5-30 Hz, and with strains that might allow detection of Galactic CCSNe. The jittering jets explosion mechanism…

We investigate the potential of neural-network based classifiers for discriminating gravitational wave bursts (GWBs) of a given canonical family (e.g. core-collapse supernova waveforms) from typical transient instrumental artifacts…

We study supernova (SN) classification using the machine learning method of the Recurrent Neural Network (RNN) in the Chinese Space Station Survey Telescope Ultra-Deep Field (CSST-UDF) photometric survey, and explore the improvement of the…

Aims: Massive stars in low-metallicity environments may produce exotic explosions such as long-duration gamma-ray bursts and pair-instability supernovae when they die as core-collapse supernovae (CCSNe). Here we determine the feasibility of…

The Pan-STARRS (PS1) Medium Deep Survey discovered over 5,000 likely supernovae (SNe) but obtained spectral classifications for just 10% of its SN candidates. We measured spectroscopic host galaxy redshifts for 3,147 of these likely SNe and…

We study high-energy (HE) neutrino production from interactions between supernova (SN) ejecta and the surrounding circumstellar material (CSM), focusing on regular Type~II and Type~IIn SNe. Using observationally inferred CSM density…

Under the assumption that jets explode all core collapse supernovae (CCSNe) I classify 14 CCSN remnants (CCSNRs) into five groups according to their morphology as shaped by jets, and attribute the classes to the specific angular momentum of…

Core-collapse supernovae (CCSNe) are the explosions of massive stars following the collapse of the stars' iron cores. Poznanski (2013) has recently suggested an observational correlation between the ejecta velocities and the inferred masses…

(Abridged) Core-collapse supernova remnants (SNRs) display complex morphologies and asymmetries, reflecting anisotropies from the explosion and early interactions with the circumstellar medium (CSM). Spectral analysis of these remnants can…