Related papers: Deep learning for multimessenger core-collapse sup…
We study the prospects of detecting continuous gravitational waves (CGWs) from spinning neutron stars (NSs), gravitationally lensed by the galactic supermassive black hole. Assuming various astrophysically motivated spatial distributions of…
Gadolinium-loading of large water Cherenkov detectors is a prime method for the detection of the Diffuse Supernova Neutrino Background (DSNB). While the enhanced neutron tagging capability greatly reduces single-event backgrounds,…
Core-collapse supernovae (CCSNe) are among the most energetic processes in our Universe and are crucial for the understanding of the formation and chemical composition of the Universe. The precise measurement of the neutrino light curve…
Gravitational-wave astronomy has opened a direct observational window onto compact-object dynamics, strong-field gravity, and cosmology. Among the transient sources accessible through this window, core-collapse supernovae (CCSNe) are…
While existing detectors would see a burst of many neutrinos from a Milky Way supernova, the supernova rate is only a few per century. As an alternative, we propose the detection of ~ 1 neutrino per supernova from galaxies within 10 Mpc, in…
In this paper, we consider the use of deep neural networks in the context of Multiple-Input-Multiple-Output (MIMO) detection. We give a brief introduction to deep learning and propose a modern neural network architecture suitable for this…
The Advanced LIGO and Advanced Virgo detectors have enabled the confident detection of dozens of mergers of black holes and neutron stars. However, the presence of detector noise transients (glitches) hinders the search for these…
Broadband frequency output of gravitational-wave detectors is a non-stationary and non-Gaussian time series data stream dominated by noise populated by local disturbances and transient artifacts, which evolve on the same timescale as the…
With GW170817 being the only multimessenger gravitational wave (GW) event with an associated kilonova detected so far, there exists a pressing need for realistic estimation of the GW localization uncertainties and rates, as well as…
Significant progress has been made in the development of an international network of gravitational wave detectors, such as TAMA300, LIGO, VIRGO, and GEO600. For these detectors, one of the most promising sources of gravitational waves are…
Most existing criteria derived from progenitor properties of core-collapse supernovae are not very accurate in predicting explosion outcomes. We present a novel look at identifying the explosion outcome of core-collapse supernovae using a…
Multi-messenger observations of gravitational waves and electromagnetic emission from compact object mergers offer unique insights into the structure of neutron stars, the formation of heavy elements, and the expansion rate of the Universe.…
SN 2008D, a core collapse supernova at a distance of 27 Mpc, was serendipitously discovered by the Swift satellite through an associated X-ray flash. Core collapse supernovae have been observed in association with long gamma-ray bursts and…
We describe a case study of translational research, applying interpretability techniques developed for computer vision to machine learning models used to search for and find gravitational waves. The models we study are trained to detect…
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…
Recently, CNN object detectors have achieved high accuracy on remote sensing images but require huge labor and time costs on annotation. In this paper, we propose a new uncertainty-based active learning which can select images with more…
Although there have now been hundreds of transient gravitational-wave detections of merging compact stars by the LIGO-Virgo-KAGRA (LVK) detector network, no continuous-wave (CW) signals have yet been discovered. To ensure that such signals,…
This paper proposes a new approach for the selection of low-energy neutrino bursts, such as the ones detected after a supernova. It exploits the temporal structure of the expected signal with respect to the more diffuse background by…
We present a methodology based on the implementation of a fully connected neural network to estimate the gravitational wave (GW) temporal evolution of the gmode fundamental resonant frequency for a Core Collapse Supernova (CCSN). To perform…
Lensed gravitational waves (GWs) provide a new window into the study of dark matter substructures, yet the faint interference signatures they produce are buried in detector noise. To address this challenge, we develop a deep learning…