Related papers: LSTM and CNN application for core-collapse superno…
Clinical medical data, especially in the intensive care unit (ICU), consist of multivariate time series of observations. For each patient visit (or episode), sensor data and lab test results are recorded in the patient's Electronic Health…
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…
All scientific claims of gravitational wave discovery to date rely on the offline statistical analysis of candidate observations in order to quantify significance relative to background processes. The current foundation in such offline…
In this work, we investigate the feasibility and effectiveness of employing deep learning algorithms for automatic recognition of the modulation type of received wireless communication signals from subsampled data. Recent work considered a…
With the upcoming Vera C.~Rubin Observatory Legacy Survey of Space and Time (LSST), it is expected that only $\sim 0.1\%$ of all transients will be classified spectroscopically. To conduct studies of rare transients, such as Type I…
Subject to intricate environmental variables, the precise classification of jamming signals holds paramount significance in the effective implementation of anti-jamming strategies within communication systems. In light of this imperative,…
Gravitational-wave searches for cosmic strings are currently hindered by the presence of detector glitches, some classes of which strongly resemble cosmic string signals. This confusion greatly reduces the efficiency of searches. A…
Learning with noisy labels (LNL) has been extensively studied, with existing approaches typically following a framework that alternates between clean sample selection and semi-supervised learning (SSL). However, this approach has a…
Machine Learning (ML) algorithms are becoming popular in cosmology for extracting valuable information from cosmological data. In this paper, we evaluate the performance of a Convolutional Neural Network (CNN) trained on matter density…
Live cell microscopy sequences exhibit complex spatial structures and complicated temporal behaviour, making their analysis a challenging task. Considering cell segmentation problem, which plays a significant role in the analysis, the…
Recent advancements in gravitational wave astronomy have seen the application of convolutional neural networks (CNNs) in signal detection from compact binary coalescences. This study presents a comparative analysis of two CNN architectures:…
Efficient searches for gravitational waves from compact binary coalescence are crucial for gravitational wave observations. We present a proof-of-concept for a method that utilizes a neural network taking an SNR map, a stack of SNR time…
A major challenge of particle physics is determining the neutrino mass ordering (MO). Due to matter effects, the flavor content of the neutrino flux from a Core-Collapse Supernova (CCSN) depends on the true neutrino MO resulting in markedly…
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…
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…
The utilization of Very Low Frequency (VLF) electromagnetic signals in navigation systems is widespread. However, the non-stationary behavior of lightning signals can affect VLF electromagnetic signal transmission. Accurately classifying…
The Zwicky Transient Facility (ZTF) was expected to detect more than one strong gravitationally-lensed supernova (glSN) per year, but only one event was identified in the first four years of the survey. This work investigates selection…
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…
We release CosmoDC2_BCO, a synthetic catalog of gravitational-wave events and electromagnetic counterparts associated with galaxies from CosmoDC2. The catalog provides intrinsic and extrinsic source parameters, signal-to-noise ratios,…
The coalescence of a binary neutron star (BNS) pair is expected to produce gravitational waves (GW) and electromagnetic (EM) radiation, both of which may be detectable with currently available instruments. We describe a search for a…