Related papers: A Search for Binary Black Hole Mergers in LIGO O1-…
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…
The first observational run of the Advanced LIGO detectors, from September 12, 2015 to January 19, 2016, saw the first detections of gravitational waves from binary black hole mergers. In this paper we present full results from a search for…
We introduce a new technique to search for gravitational wave events from compact binary mergers that produce a clear signal only in a single gravitational wave detector, and marginal signals in other detectors. Such a situation can arise…
We present a convolutional neural network, designed in the auto-encoder configuration that can detect and denoise astrophysical gravitational waves from merging black hole binaries, orders of magnitude faster than the conventional…
The recent Nobel-prize-winning detections of gravitational waves from merging black holes and the subsequent detection of the collision of two neutron stars in coincidence with electromagnetic observations have inaugurated a new era of…
The recent Nobel-prize-winning detections of gravitational waves from merging black holes and the subsequent detection of the collision of two neutron stars in coincidence with electromagnetic observations have inaugurated a new era of…
In this work, we use the coherent WaveBurst (cWB) pipeline enhanced with machine learning (ML) to search for binary black hole (BBH) mergers in the Advanced LIGO-Virgo strain data from the third observing run (O3). We detect, with…
In August 2017, the first detection of a binary neutron star merger, GW170817, made it possible to study neutron stars in compact binary systems using gravitational waves. Despite being the loudest gravitational wave event detected to date…
The detection of gravitational waves from the merger of binary black holes by the LIGO Collaboration has opened a new window to astrophysics. With the sensitivities of ground based detectors in the coming years we can only detect the local…
It may soon be possible for Advanced LIGO to detect hundreds of binary black hole mergers per year. We show how the accumulation of many such measurements will allow for the detection of gravitational-wave memory: a permanent displacement…
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…
We explore machine learning methods to detect gravitational waves (GW) from binary black hole (BBH) mergers using deep learning (DL) algorithms. The DL networks are trained with gravitational waveforms obtained from BBH mergers with…
Gravitational wave detection has opened up new avenues for exploring and understanding some of the fundamental principles of the universe. The optimal method for detecting modelled gravitational-wave events involves template-based matched…
We introduce the use of deep learning ensembles for real-time, gravitational wave detection of spinning binary black hole mergers. This analysis consists of training independent neural networks that simultaneously process strain data from…
Recent developments in deep learning techniques have offered an alternative and complementary approach to traditional matched filtering methods for the identification of gravitational wave (GW) signals. The rapid and accurate identification…
We present the results from three gravitational-wave searches for coalescing compact binaries with component masses above 1$\mathrm{M}_\odot$ during the first and second observing runs of the Advanced gravitational-wave detector network.…
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…
Gravitational wave detection requires an in-depth understanding of the physical properties of gravitational wave signals, and the noise from which they are extracted. Understanding the statistical properties of noise is a complex endeavor,…
The Coherent WaveBurst (cWB) search algorithm identifies generic gravitational wave (GW) signals in the LIGO-Virgo strain data. We propose a machine learning (ML) method to optimize the pipeline sensitivity to the special class of GW…
Burst searches identify gravitational-wave (GW) signals in the detector data without use of a specific signal model, unlike the matched-filter searches that correlate data with simulated signal waveforms (templates). While matched filters…