相关论文: Amplifying the Chirp: Using Deep Learning (U-Nets)…
In the coming years gravitational-wave detectors will undergo a series of improvements, with an increase in their detection rate by about an order of magnitude. Routine detections of gravitational-wave signals promote novel astrophysical…
Advanced LIGO data contains numerous noise transients, or "glitches", that have been shown to reduce the sensitivity of matched filter searches for gravitational waves from compact binaries by increasing the rate at which random…
In searching for continuous gravitational waves over very many ($\approx 10^{17}$) templates , clustering is a powerful tool which increases the search sensitivity by identifying and bundling together candidates that are due to the same…
We have implemented likelihood testing of the performance of an optimal filter within the online analysis of AURIGA, a sub-Kelvin resonant-bar gravitational wave detector. We demonstrate the effectiveness of this technique in discriminating…
Data quality assessment plays an essential role in the quest to detect gravitational wave signals in data from the LIGO and Virgo interferometric gravitational wave detectors. Interferometer data contains a high rate of noise transients…
Seven years after the first direct detection of gravitational waves, from the collision of two black holes, the field of gravitational wave astronomy is firmly established. A first detection of continuous gravitational waves from…
Searches for gravitational waves crucially depend on exact signal processing of noisy strain data from gravitational wave detectors, which are known to exhibit significant non-Gaussian behavior. In this paper, we study two distinct…
Since the first detection of gravitational waves in 2015 by LIGO from the binary black hole merger GW150914, gravitational-wave astronomy has developed significantly, with over 200 compact binary merger events cataloged. The use of neural…
The presence of noise is common in signal processing regardless the signal type. Deep neural networks have shown good performance in noise removal, especially on the image domain. In this work, we consider deep neural networks as a…
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…
We present a method to characterize the noise in ground-based gravitational-wave observatories such as the Laser Gravitational-Wave Observatory (LIGO). This method uses linear regression algorithms such as the least absolute shrinkage and…
This decade will see the first direct detections of gravitational waves by observatories such as Advanced LIGO and Virgo. Among the prime sources are coalescences of binary neutron stars and black holes, which are ideal probes of dynamical…
The detection of quasi-periodic sources of gravitational waves requires the accumulation of signal-to-noise over long observation times. If not removed, Earth-motion induced Doppler modulations, and intrinsic variations of the…
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…
Deep learning had already demonstrated its power in medical images, including denoising, classification, segmentation, etc. All these applications are proposed to automatically analyze medical images beforehand, which brings more…
Searching the data of gravitational-wave detectors for signals from compact binary mergers is a computationally demanding task. Recently, machine learning algorithms have been proposed to address current and future challenges. However, the…
Because of the small strain amplitudes of gravitational-wave (GW) signals, unveiling them in the presence of detector/environmental noise is challenging. For visualizing the signals and extracting its waveform for a comparison with…
The gravitational wave detection problem is challenging because the noise is typically overwhelming. Convolutional neural networks (CNNs) have been successfully applied, but require a large training set and the accuracy suffers…
Nearly a century after Einstein first predicted the existence of gravitational waves, a global network of earth-based gravitational wave observatories is seeking to directly detect this faint radiation using precision laser interferometry.…
The detection of gravitational waves from compact binary mergers by LIGO has opened the era of gravitational wave astronomy, revealing a previously hidden side of the cosmos. To maximize the reach of the existing LIGO observatory…