相关论文: Contrastive self-supervised convolutional autoenco…
The detection and reconstruction of gravitational waves from core-collapse supernovae (CCSN) present significant challenges due to the highly stochastic nature of the signals and the complexity of detector noise. In this work, we introduce…
We describe a search and classification procedure for gravitational waves emitted by core-collapse supernova (CCSN) explosions, using a convolutional neural network (CNN) combined with an event trigger generator known as Wavelet Detection…
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…
Core-Collapse Supernovae (CCSNe) remain a critical focus in the search for gravitational waves (GWs) in modern astronomy. Their detection and subsequent analysis will enhance our understanding of the explosion mechanisms in massive stars.…
The next generation of gravitational wave detectors will improve the detection prospects for gravitational waves from core-collapse supernovae. The complex astrophysics involved in core-collapse supernovae pose a significant challenge to…
Core-collapse supernovae (CCSNe) are powerful sources of gravitational waves (GWs). These signals propagate essentially unobstructed, providing a unique probe of the supernova central engine. In this work, we investigate parameter…
Core-collapse supernovae (CCSNe) are a potential source for ground-based gravitational wave detectors, as their predicted emission peaks in the detectors' frequency band. Typical searches for gravitational wave bursts reconstruct signals…
A detection of a core-collapse supernova signal with an Advanced LIGO and Virgo gravitational-wave detector network will allow us to measure astrophysical parameters of the source. In real advanced gravitational-wave detector data there are…
The advent of sensitive gravitational wave (GW) detectors, coupled with wide-field, high cadence optical time-domain surveys, raises the possibility of the first joint GW-electromagnetic (EM) detections of core-collapse supernovae (CCSNe).…
Nearby core-collapse supernovae (CCSNe) are powerful multi-messenger sources for gravitational-wave, neutrino and electromagnetic telescopes as they emit gravitational waves in the ideal frequency band for ground based detectors. Once a…
Variational autoencoders are powerful algorithms for identifying dominant latent structure in a single dataset. In many applications, however, we are interested in modeling latent structure and variation that are enriched in a target…
Core-collapse supernovae (CCSNe) are prime candidates for gravitational-wave detectors. The analysis of their complex waveforms can potentially provide information on the physical processes operating during the collapse of the iron cores of…
A detection of a core-collapse supernova (CCSN) gravitational-wave (GW) signal with an Advanced LIGO and Virgo detector network may allow us to measure astrophysical parameters of the dying massive star. GWs are emitted from deep inside the…
We demonstrate how a morphological veto involving Bayesian statistics can improve the receiver-operating characteristic (ROC) curves of the current search for core-collapse supernovae (CCSNe) as implemented by the coherent Waveburst (cWB)…
Gravitational waves (GW), predicted by Einstein's General Theory of Relativity, provide a powerful probe of astrophysical phenomena and fundamental physics. In this work, we propose an unsupervised anomaly detection method using variational…
Core-collapse supernovae (CCSNe) are regularly observed electromagnetically, prompting targetted searches for their gravitational-wave emission. However, there are scenarios where these powerful explosions may not have any observable…
$Context.$ Core-collapse supernovae (CCSNe) are expected to emit gravitational wave signals that could be detected by current and future generation interferometers within the Milky Way and nearby galaxies. The stochastic nature of the…
The Variational Autoencoder (VAE) is known to suffer from the phenomenon of \textit{posterior collapse}, where the latent representations generated by the model become independent of the inputs. This leads to degenerated representations of…
Supernovae (SNe) come in various flavors and are classified into different types based on emission and absorption lines in their spectra. SN candidates are now abundant with the advent of large systematic sky surveys like the Zwicky…
Gravitational waves (GWs) can provide crucial information about the central engines of core-collapse supernovae (CCSNe). In order to unveil the nature of GW emission in CCSNe, we apply perturbative analyses with the same underlying…