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Fast-pairwise neutrino oscillations potentially affect many aspects of core-collapse supernova (CCSN): the explosion mechanism, neutrino signals, and nucleosynthesis in the ejecta. This particular mode of collective neutrino oscillations…
A gravitational-wave background (GWB) arising from the superposition of numerous unresolved gravitational-wave signals has yet to be detected. Potential contributing sources to such a background include compact binary coalescences (CBCs)…
Among astrophysical sources in the Advanced LIGO and Advanced Virgo detectors' frequency band are rotating non-axisymmetric neutron stars emitting long-lasting, almost-monochromatic gravitational waves. Searches for these continuous…
Effective and powerful methods for denoising real electrocardiogram (ECG) signals are important for wearable sensors and devices. Deep Learning (DL) models have been used extensively in image processing and other domains with great success…
We present the gravitational wave predictions from two-dimensional core collapse supernova (CCSN) simulations initiated from two nearly identical progenitors that have significantly different internal structures due to their late-stage…
Relic gravitational waves (RGWs) from early universe carry fundamental information, so it's extraordinarily important to search RGW signals from data of observatories like LIGO-Virgo network. Here, focusing on typical RGWs from inflation…
The Vera Rubin Observatory's Legacy Survey of Space and Time (LSST) is expected to revolutionize time-domain optical astronomy as we know it. With its unprecedented depth, the LSST will survey the southern hemisphere sky, generating nearly…
Real-time noise regression algorithms are crucial for maximizing the science outcomes of the LIGO, Virgo, and KAGRA gravitational-wave detectors. This includes improvements in the detectability, source localization and pre-merger…
In the last few years, machine learning techniques, in particular convolutional neural networks, have been investigated as a method to replace or complement traditional matched filtering techniques that are used to detect the…
LSST's wide-field of view and sensitivity will revolutionize studies of the transient sky by finding extraordinary numbers of new transients every night. The recent discovery of a kilonova counterpart to LIGO/Virgo's first detection of…
Network intrusions are a significant problem in all industries today. A critical part of the solution is being able to effectively detect intrusions. With recent advances in artificial intelligence, current research has begun adopting deep…
The development of accurate methods for multi-label classification (MLC) of remote sensing (RS) images is one of the most important research topics in RS. The MLC methods based on convolutional neural networks (CNNs) have shown strong…
Weak gravitational lensing is one of the most promising cosmological probes of the late universe. Several large ongoing (DES, KiDS, HSC) and planned (LSST, EUCLID, WFIRST) astronomical surveys attempt to collect even deeper and larger scale…
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…
Current searches for gravitational waves (GWs) from black hole binaries using the LIGO and Virgo observatories are limited to analytical models for systems with black hole spins aligned (or anti-aligned) with the orbital angular momentum of…
The next generation of data-intensive surveys are bound to produce a vast amount of data, which can be dealt with using machine-learning methods to explore possible correlations within the multi-dimensional parameter space. We explore the…
The life detection method based on a single type of information source cannot meet the requirement of post-earthquake rescue due to its limitations in different scenes and bad robustness in life detection. This paper proposes a method based…
The next Galactic core-collapse supernova (SN) should yield a large number of observed neutrinos. Using Bayesian techniques, we show that with an SN at a known distance up to 25 kpc, the neutrino events in a water Cherenkov detector similar…
In this paper, we study an application of deep learning to the advanced LIGO and advanced Virgo coincident detection of gravitational waves (GWs) from compact binary star mergers. This deep learning method is an extension of the Deep…
Like in many other research fields, recent developments in computational imaging have focused on developing machine learning (ML) approaches to tackle its main challenges. To improve the performance of computational imaging algorithms,…