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Gravitational wave data are often contaminated by non-Gaussian noise transients, glitches, which can bias the inference of astrophysical signal parameters. Traditional approaches either subtract glitches in a pre-processing step, or a…

广义相对论与量子宇宙学 · 物理学 2025-08-01 Ann-Kristin Malz , John Veitch

The Laser Interferometer Space Antenna (LISA) is expected to detect gravitational radiation from a large number of compact binary systems. We present a method by which these signals can be identified and have their parameters estimated. Our…

广义相对论与量子宇宙学 · 物理学 2009-11-11 Richard Umstätter , Nelson Christensen , Martin Hendry , Renate Meyer , Vimal Simha , John Veitch , Sarah Vigeland , Graham Woan

Separating a stochastic gravitational wave background (SGWB) from noise is a challenging statistical task. One approach to establishing a detection criterion for the SGWB is using Bayesian evidence. If the evidence ratio (Bayes factor)…

天体物理仪器与方法 · 物理学 2025-09-17 Federico Pozzoli , Jonathan Gair , Riccardo Buscicchio , Lorenzo Speri

The analysis of gravitational wave interferometer data requires estimates for the noise covariance matrix. For stationary noise, this amounts to estimating the power spectrum. Classical methods such as Welch averaging are used in many…

广义相对论与量子宇宙学 · 物理学 2024-03-05 Toral Gupta , Neil Cornish

In this article, which will appear as a chapter in the Handbook of Gravitational Wave Astronomy, we will describe the detection of gravitational waves with space-based interferometric gravitational wave observatories. We will provide an…

广义相对论与量子宇宙学 · 物理学 2022-01-27 Jonathan R Gair , Martin Hewitson , Antoine Petiteau , Guido Mueller

The Laser Interferometer Space Antenna (LISA) is a planned space-based gravitational wave telescope with the goal of measuring gravitational waves in the milli-Hertz frequency band, which is dominated by millions of Galactic binaries. While…

天体物理仪器与方法 · 物理学 2023-07-11 Stefan H. Strub , Luigi Ferraioli , Cédric Schmelzbach , Simon C. Stähler , Domenico Giardini

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…

广义相对论与量子宇宙学 · 物理学 2025-07-22 Bo Liang , He Wang

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…

天体物理仪器与方法 · 物理学 2025-03-10 Nir Guttman , Paul D. Lasky , Eric Thrane

Understanding the properties of transient gravitational waves and their sources is of broad interest in physics and astronomy. Bayesian inference is the standard framework for astro-physical measurement in transient gravitational-wave…

广义相对论与量子宇宙学 · 物理学 2020-10-07 Rory Smith , Gregory Ashton , Avi Vajpeyi , Colm Talbot

The upcoming gravitational wave (GW) observatory LISA will measure the parameters of sources like extreme-mass-ratio inspirals (EMRIs) to exquisite precision. These measurements will also be sensitive to perturbations to the vacuum,…

广义相对论与量子宇宙学 · 物理学 2025-06-18 Shubham Kejriwal , Francisco Duque , Alvin J. K. Chua , Jonathan Gair

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…

广义相对论与量子宇宙学 · 物理学 2025-08-07 Charlie Hoy , Sarp Akcay , Jake Mac Uilliam , Jonathan E. Thompson

Gravitational wave models are used to infer the properties of black holes in merging binaries from the observed gravitational wave signals through Bayesian inference. Although we have access to a large collection of signal models that are…

广义相对论与量子宇宙学 · 物理学 2022-10-19 Charlie Hoy

The detection of a stochastic background of gravitational waves could significantly impact our understanding of the physical processes that shaped the early Universe. The challenge lies in separating the cosmological signal from other…

广义相对论与量子宇宙学 · 物理学 2014-11-20 Matthew R. Adams , Neil J. Cornish

Estimating the parameters of gravitational wave signals detected by ground-based detectors requires an understanding of the properties of the detectors' noise. In particular, the most commonly used likelihood function for gravitational wave…

Posterior distributions on parameters computed from experimental data using Bayesian techniques are only as accurate as the models used to construct them. In many applications these models are incomplete, which both reduces the prospects of…

广义相对论与量子宇宙学 · 物理学 2015-06-23 Christopher J. Moore , Jonathan R. Gair

The number of astrophysical sources detected by Advanced LIGO and Virgo is expected to increase as the detectors approach their design sensitivity. Gravitational wave detectors are also sensitive to transient noise sources created by the…

天体物理仪器与方法 · 物理学 2018-07-25 Jade Powell

The development of search algorithms for gravitational wave sources in the LISA data stream is currently a very active area of research. It has become clear that not only does difficulty lie in searching for the individual sources, but in…

广义相对论与量子宇宙学 · 物理学 2009-10-05 Edward K. Porter

Gravitational waves modulate the apparent frequencies of other periodic signals. Low-frequency gravitational waves could therefore be detected by observing frequency modulations in signals from higher-frequency sources, e.g., those from…

广义相对论与量子宇宙学 · 物理学 2024-08-09 Jakob Stegmann , Sander M. Vermeulen

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…

广义相对论与量子宇宙学 · 物理学 2015-03-17 Walter Del Pozzo , John Veitch , Alberto Vecchio

The main goal of the LISA Pathfinder (LPF) mission is to fully characterize the acceleration noise models and to test key technologies for future space-based gravitational-wave observatories similar to the eLISA concept. The data analysis…