Related papers: Using weighting algorithms to refine source direct…

Ground-based gravitational wave laser interferometers (LIGO, GEO-600, Virgo and Tama-300) have now reached high sensitivity and duty cycle. We present a Bayesian evidence-based approach to the search for gravitational waves, in particular…

It is expected that gravitational waves, similar to electromagnetic waves, can be gravitationally lensed by intervening matters, producing multiple instances of the same signal arriving at different times from different apparent luminosity…

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…

We describe a coherent network algorithm for detection and reconstruction of gravitational wave bursts. The algorithm works for two and more arbitrarily aligned detectors and can be used for both all-sky and triggered burst searches. We…

We present a method for detection and reconstruction of the gravitational-wave (GW) transients with the networks of advanced detectors. Originally designed to search for transients with the initial GW detectors, it uses significantly…

We propose a coherent method for the detection and reconstruction of gravitational wave signals for a network of interferometric detectors. The method is derived using the likelihood functional for unknown signal waveforms. In the standard…

Searches for gravitational wave signals which do not have a precise model describing the shape of their waveforms are often performed using power detectors based on a quadratic form of the data. A new, optimal method of generalizing these…

Gravitational wave astronomy has been already a well-established research domain for many years. Moreover, after the detection by LIGO/Virgo collaboration, in 2017, of the first gravitational wave signal emitted during the collision of a…

An observation of gravitational waves is a trigger of the multi-messenger search of an astronomical event. A combination of the data from two or three gravitational wave telescopes indicates the location of a source and low-latency data…

We demonstrate unprecedented accuracy for rapid gravitational-wave parameter estimation with deep learning. Using neural networks as surrogates for Bayesian posterior distributions, we analyze eight gravitational-wave events from the first…

We present two search algorithms that implement logarithmic tiling of the time-frequency plane in order to efficiently detect astrophysically unmodeled bursts of gravitational radiation. The first is a straightforward application of the…

Space-based gravitational wave (GW) detectors will be able to observe signals from sources that are otherwise nearly impossible from current ground-based detection. Consequently, the well established signal detection method, matched…

Modelling noise in gravitational-wave observatories is crucial for accurately inferring the properties of gravitational-wave sources. We introduce a transdimensional Bayesian approach to characterise the noise in ground-based…

Inferring the astrophysical parameters of coalescing compact binaries is a key science goal of the upcoming advanced LIGO-Virgo gravitational-wave detector network and, more generally, gravitational-wave astronomy. However, current…

Machine learning has emerged as a popular and powerful approach for solving problems in astrophysics. We review applications of machine learning techniques for the analysis of ground-based gravitational-wave detector data. Examples include…

We investigate the class of quadratic detectors (i.e., the statistic is a bilinear function of the data) for the detection of poorly modeled gravitational transients of short duration. We point out that all such detection methods are…

This review provides a conceptual and technical survey of methods for parameter estimation of gravitational wave signals in ground-based interferometers such as LIGO and Virgo. We introduce the framework of Bayesian inference and provide an…

The reliability of the first detection is one of the most interesting challenges for the gravitational wave community. To increase the detection confidence, the LIGO and Virgo collaborations have already started coincident observations…

We report on the construction of a deep convolutional neural network that can reproduce the sensitivity of a matched-filtering search for binary black hole gravitational-wave signals. The standard method for the detection of well modeled…

We present a new method which accounts for changes in the properties of gravitational-wave detector noise over time in the PyCBC search for gravitational waves from compact binary coalescences. We use information from LIGO data quality…