Related papers: Improving the background of gravitational-wave sea…
The LIGO Scientific Collaboration and Virgo Collaboration have carried out joint searches in LIGO and Virgo data for periodic continuous gravitational waves. These analyses range from targeted searches for gravitational-wave signals from…
One of the key challenges of real-time detection and parameter estimation of gravitational waves from compact binary mergers is the computational cost of conventional matched-filtering and Bayesian inference approaches. In particular, the…
In this article, we introduce a methodology based on an analytical model of a damped harmonic oscillator subject to random forcing to generate transient gravitational wave signals. Such a model incorporates a simulated linear high-frequency…
Machine learning has become an effective tool for processing the extensive data sets produced by large physics experiments. Gravitational-wave detectors are now listening to the universe with quantum-enhanced sensitivity, accomplished with…
Gravitational wave echoes have been proposed as a smoking-gun signature of exotic compact objects with near-horizon structure. Recently there have been observational claims that echoes are indeed present in stretches of data from Advanced…
The LIGO Scientific Collaboration and the Virgo Collaboration have cataloged eleven confidently detected gravitational-wave events during the first two observing runs of the advanced detector era. All eleven events were consistent with…
We present a comprehensive study of the effectiveness of Convolution Neural Networks (CNNs) to detect long duration transient gravitational-wave signals lasting $O(hours-days)$ from isolated neutron stars. We determine that CNNs are robust…
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…
An important goal for LIGO (the Laser Interferometer Gravitational-Wave Observatory) and Virgo is to find periodic sources of gravitational waves. The LIGO and Virgo detectors are sensitive to a variety of noise of non-astrophysical origin,…
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…
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…
We present results from searches of recent LIGO and Virgo data for continuous gravitational wave signals (CW) from spinning neutron stars and for a stochastic gravitational wave background (SGWB). The first part of the talk is devoted to CW…
The detection of gravitational waves from compact binary coalescences has provided significant insights into our Universe, and the discovery of new and unique gravitational wave candidates from independent searches remains an ongoing field…
With the advent of gravitational-wave astronomy and the discovery of more compact binary coalescences, data quality improvement techniques are desired to handle the complex and overwhelming noise in gravitational wave (GW) observational…
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,…
Long-lived gravitational wave (GW) transients have received interest in the last decade, as the sensitivity of LIGO and Virgo increases. Such signals, lasting between 10 and 1000s, can come from a variety of sources, including accretion…
We present here the latest development of a machine-learning pipeline for pre-merger alerts from gravitational waves coming from binary neutron stars. This work starts from the convolutional neural networks introduced in our previous paper…
The goal of the Laser Interferometric Gravitational-Wave Observatory (LIGO) is to detect and study gravitational waves of astrophysical origin. Direct detection of gravitational waves holds the promise of testing general relativity in the…
We investigate the use of Convolutional Neural Networks (including the modern ConvNeXt network family) to classify transient noise signals (i.e.~glitches) and gravitational waves in data from the Advanced LIGO detectors. First, we use…
The detection of gravitational waves by the LIGO-Virgo-KAGRA collaboration has ushered in a new era of observational astronomy, emphasizing the need for rapid and detailed parameter estimation and population-level analyses. Traditional…