Related papers: Detecting and Denoising Gravitational Wave Signals…
We assess total-variation methods to denoise gravitational-wave signals in real noise conditions, by injecting numerical-relativity waveforms from core-collapse supernovae and binary black hole mergers in data from the first observing run…
In this paper, we report on the construction of a deep Artificial Neural Network (ANN) to localize simulated gravitational wave signals in the sky with high accuracy. We have modelled the sky as a sphere and have considered cases where the…
During their first observational run, the two Advanced LIGO detectors attained an unprecedented sensitivity, resulting in the first direct detections of gravitational-wave signals and GW151226, produced by stellar-mass binary black hole…
This work introduces a novel deep learning-based approach for gravitational wave anomaly detection, aiming to overcome the limitations of traditional matched filtering techniques in identifying unknown waveform gravitational wave signals.…
A small fraction of the gravitational-wave (GW) signals that will be detected by second and third generation detectors are expected to be strongly lensed by galaxies and clusters, producing multiple observable copies. While optimal Bayesian…
Gravitational waves are now routinely detected from compact binary mergers, with binary neutron star mergers being of note for multi-messenger astronomy as they have been observed to produce electromagnetic counterparts. Novel search…
The observation of gravitational waves emitted during the merging phase of compact binary coalescing objects has opened a new field of investigation in fundamental physics. It is now possible to test the predictions of General Relativity…
In 2016, LIGO and Virgo announced the first observation of gravitational waves from a binary black hole merger, known as GW150914. To establish the confidence of this detection, large-scale scientific workflows were used to measure the…
The discovery of the astrophysical events GW150926 and GW151226 has experimentally confirmed the existence of gravitational waves (GW) and has demonstrated the existence of binary stellar-mass black hole systems. This finding marks the…
We present a novel machine-learning approach to estimate selection effects in gravitational-wave observations. Using techniques similar to those commonly employed in image classification and pattern recognition, we train a series of…
Convolutional Neural Networks (CNNs) have demonstrated potential for the real-time analysis of data from gravitational-wave detector networks for the specific case of signals from coalescing compact-object binaries such as black-hole…
The phenomenon of Gravitational Wave (GW) analysis has grown in popularity as technology has advanced and the process of observing gravitational waves has become more precise. Although the sensitivity and the frequency of observation of GW…
Machine learning can be a powerful tool to discover new signal types in astronomical data. We here apply it to search for long-duration transient gravitational waves triggered by pulsar glitches, which could yield physical insight into the…
GW170817 has led to the first example of multi-messenger astronomy with observations from gravitational wave interferometers and electromagnetic telescopes combined to characterise the source. However, detections of the early inspiral phase…
Context: The LIGO consortium announced the first direct detection of gravitation wave event GW150914 from two merging black holes; however the nature of the black holes are still not clear. Aims: We study whether electromagnetic radiation…
The higher-multipoles of gravitational wave signals from coalescing compact binaries play a vital role in the accurate reconstruction of source properties, bringing about a deeper and nuanced understanding of fundamental physics and…
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…
Gravitational wave astronomy has been firmly established with the detection of gravitational waves from the merger of ten stellar mass binary black holes and a neutron star binary. This paper reports on the all-sky search for gravitational…
The first detection of a gravitational-wave signal of a coalescence of two black holes marked the beginning of the era of gravitational-wave astronomy, which opens exciting new possibilities in the fields of astronomy, astrophysics and…
We present a novel Machine Learning (ML) based strategy to search for binary black hole (BBH) mergers in data from ground-based gravitational wave (GW) observatories. This is the first ML-based search that not only recovers all the compact…