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Inferring the properties of colliding black holes from gravitational-wave observations is subject to systematic errors arising from modelling uncertainties. Although the accuracy of each model can be calculated through comparison to…

General Relativity and Quantum Cosmology · Physics 2025-08-07 Charlie Hoy , Sarp Akcay , Jake Mac Uilliam , Jonathan E. Thompson

Direct detection of gravitational waves by pulsar timing arrays will become feasible over the next few years. In the low frequency regime ($10^{-7}$ Hz -- $10^{-9}$ Hz), we expect that a superposition of gravitational waves from many…

Instrumentation and Methods for Astrophysics · Physics 2015-06-15 Justin Ellis , Xavier Siemens , Rutger van Haasteren

Pulsar timing now has a rich history in placing limits on the stochastic background of gravitational waves, and we plan soon to reach the sensitivity where we can detect, not just place limits on, the stochastic background. However, the…

High Energy Astrophysical Phenomena · Physics 2015-06-03 Andrea N. Lommen

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…

Instrumentation and Methods for Astrophysics · Physics 2025-03-10 Nir Guttman , Paul D. Lasky , Eric Thrane

Second generation interferometric gravitational wave detectors, such as Advanced LIGO and Advanced Virgo, are expected to begin operation by 2015. Such instruments plan to reach sensitivities that will offer the unique possibility to test…

General Relativity and Quantum Cosmology · Physics 2015-03-17 Walter Del Pozzo , John Veitch , Alberto Vecchio

Future searches for a gravitational-wave background using Earth-based gravitational-wave detectors might be impacted by correlated noise sources. A well known example are the Schumann resonances, which are extensively studied in the context…

General Relativity and Quantum Cosmology · Physics 2022-04-20 Kamiel Janssens , Thomas A. Callister , Nelson Christensen , Michael W. Coughlin , Ioannis Michaloliakos , Jishnu Suresh , Nick van Remortel

Analysis of high-precision timing observations of an array of approx. 20 millisecond pulsars (a so-called "timing array") may ultimately result in the detection of a stochastic gravitational-wave background. The feasibility of such a…

The Bayesian evidence is a key tool in model selection, allowing a comparison of models with different numbers of parameters. Its use in analysis of cosmological models has been limited by difficulties in calculating it, with current…

Cosmology and Nongalactic Astrophysics · Physics 2023-02-01 Juan Garcia-Bellido

Continuous nanohertz gravitational waves from individual supermassive black hole binaries may be detectable with pulsar timing arrays. A novel search strategy is developed, wherein intrinsic achromatic spin wandering is tracked…

We describe the consistency testing of a new code for gravitational wave signal parameter estimation in known pulsar searches. The code uses an implementation of nested sampling to explore the likelihood volume. Using fake signals and…

High Energy Astrophysical Phenomena · Physics 2015-06-04 M. Pitkin , C. Gill , J. Veitch , E. Macdonald , G. Woan

Gravitational wave searches rely on a combination of methods, including matched filtering, coherent analyses, and more recent machine learning based pipelines. For compact binary coalescences, where signals originate from the relativistic…

General Relativity and Quantum Cosmology · Physics 2026-03-11 Lorenzo Mobilia , Tito Dal Canton , Gianluca Maria Guidi

Efforts to detect gravitational waves by timing an array of pulsars have focused traditionally on stationary gravitational waves: e.g., stochastic or periodic signals. Gravitational wave bursts --- signals whose duration is much shorter…

Instrumentation and Methods for Astrophysics · Physics 2014-11-20 Lee Samuel Finn , Andrea N. Lommen

Searches for gravitational-wave bursts (transient signals, typically of unknown waveform) require identification of weak signals in background detector noise. The sensitivity of such searches is often critically limited by non-Gaussian…

General Relativity and Quantum Cosmology · Physics 2013-10-02 Thomas S. Adams , Duncan Meacher , James Clark , Patrick J. Sutton , Gareth Jones , Ariana Minot

The quest to observe gravitational waves challenges our ability to discriminate signals from detector noise. This issue is especially relevant for transient gravitational waves searches with a robust eyes wide open approach, the so called…

Instrumentation and Methods for Astrophysics · Physics 2017-04-19 S. Vinciguerra , M. Drago , G. A. Prodi , S. Klimenko , C. Lazzaro , V. Necula , F. Salemi , V. Tiwari , M. C. Tringali , G. Vedovato

We present and assess a Bayesian method to interpret gravitational wave signals from binary black holes. Our method directly compares gravitational wave data to numerical relativity simulations. This procedure bypasses approximations used…

The recent announcement of evidence for a stochastic background of gravitational waves (GWB) in pulsar timing array (PTA) data has piqued interest across the scientific community. A combined analysis of all currently available data holds…

Instrumentation and Methods for Astrophysics · Physics 2025-09-01 Serena Valtolina , Rutger van Haasteren

We describe a novel approach to the detection and parameter estimation of a non\textendash Gaussian stochastic background of gravitational waves. The method is based on the determination of relevant statistical parameters using importance…

General Relativity and Quantum Cosmology · Physics 2023-08-22 Riccardo Buscicchio , Anirban Ain , Matteo Ballelli , Giancarlo Cella , Barbara Patricelli

Numerical relativity (NR) enables the study of physics in strong and dynamical gravitational fields and provides predictions for the gravitational-wave signals produced by merging black holes. Despite the impressive accuracy of modern…

General Relativity and Quantum Cosmology · Physics 2025-10-15 Richard Dyer , Christopher J. Moore

Gaussian process (GP) regression is a Bayesian nonparametric method for regression and interpolation, offering a principled way of quantifying the uncertainties of predicted function values. For the quantified uncertainties to be…

Statistics Theory · Mathematics 2025-08-22 Masha Naslidnyk , Motonobu Kanagawa , Toni Karvonen , Maren Mahsereci