Related papers: Transient Classification in low SNR Gravitational …
In recent years, improvements in Deep Learning (DL) techniques towards Gravitational Wave (GW) astronomy have led to a significant rise in the development of various classification algorithms that have been successfully employed to extract…
The LIGO observatories detect gravitational waves through monitoring changes in the detectors' length down to below $10^{-19}$\,$m/\sqrt{Hz}$ variation---a small fraction of the size of the atoms that make up the detector. To achieve this…
Despite achieving sensitivities capable of detecting the extremely small amplitude of gravitational waves (GWs), LIGO and Virgo detector data contain frequent bursts of non-Gaussian transient noise, commonly known as 'glitches'. Glitches…
Compact binary systems emit gravitational radiation which is potentially detectable by current Earth bound detectors. Extracting these signals from the instruments' background noise is a complex problem and the computational cost of most…
Gravitational wave denoising is an ongoing task for revealing the events of compact binary objects in the universe. Recently, with the aid of deep learning, gravitational waves have been efficiently and delicately extracted from the noisy…
The noise of gravitational-wave (GW) interferometers limits their sensitivity and impacts the data quality, hindering the detection of GW signals from astrophysical sources. For transient searches, the most problematic are transient noise…
Deep learning method develops very fast as a tool for data analysis these years. Such a technique is quite promising to treat gravitational wave detection data. There are many works already in the literature which used deep learning…
We investigate and demonstrate the use of convolutional neural networks (CNNs) for the task of distinguishing between merging and non-merging galaxies in simulated images, and for the first time at high redshifts (i.e. $z=2$). We extract…
This article focuses on signal classification for deep-sea acoustic neutrino detection. In the deep sea, the background of transient signals is very diverse. Approaches like matched filtering are not sufficient to distinguish between…
The proposed Laser Interferometer Space Antenna (LISA) mission is tasked with the detection and characterization of gravitational waves from various sources in the universe. This endeavor is challenged by transient displacement and…
The increasing data volume of high-energy space monitors necessitates real-time, automated transient classification for multi-messenger follow-up. Conventional methods rely on empirical features like hardness ratios and reliable…
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…
The LIGO-Virgo-KAGRA (LVK) network of gravitational-wave (GW) detectors have observed many tens of compact binary mergers to date. Transient, non-Gaussian noise excursions, known as "glitches", can impact signal detection in various ways.…
In the context of radio galaxy classification, most state-of-the-art neural network algorithms have been focused on single survey data. The question of whether these trained algorithms have cross-survey identification ability or can be…
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…
The matched filtering paradigm is the mainstay of gravitational wave (GW) searches from astrophysical coalescing compact binaries. The compact binary coalescence (CBC) search pipelines perform the matched filter between the GW detector's…
The Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo Interferometer Collaborations have now detected all three classes of compact binary mergers: binary black hole (BBH), binary neutron star (BNS), and neutron star-black…
Gravitational-wave detection pipelines have helped to identify over one hundred compact binary mergers in the data collected by the Advanced LIGO and Advanced Virgo interferometers, whose sensitivity has provided unprecedented access to the…
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…
We show that gravitational-wave signals from compact binary mergers may be better distinguished from instrumental noise transients by using Bayesian models that look for signal coherence across a detector network. This can be achieved even…