Gravitational-Wave Data Analysis. Formalism and Sample Applications: The Gaussian Case

by: Piotr Jaranowski and Andrzej Królak

The article reviews the statistical theory of signal detection in application to analysis of deterministic gravitational-wave signals in the noise of a detector. Statistical foundations for the theory of signal detection and parameter estimation are presented. Several tools needed for both theoretical evaluation of the optimal data analysis methods and for their practical implementation are introduced. They include optimal signal-to-noise ratio, Fisher matrix, false alarm and detection probabilities, ℱ-statistic, template placement, and fitting factor. These tools apply to the case of signals buried in a stationary and Gaussian noise. Algorithms to efficiently implement the optimal data analysis techniques are discussed. Formulas are given for a general gravitational-wave signal that includes as special cases most of the deterministic signals of interest.

Gravitational Wave Detection by Interferometry (Ground and Space)

by: Matthew Pitkin and Stuart Reid and Sheila Rowan and Jim Hough

Significant progress has been made in recent years on the development of gravitational-wave detectors. Sources such as coalescing compact binary systems, neutron stars in low-mass X-ray binaries, stellar collapses and pulsars are all possible candidates for detection. The most promising design of gravitational-wave detector uses test masses a long distance apart and freely suspended as pendulums on Earth or in drag-free spacecraft. The main theme of this review is a discussion of the mechanical and optical principles used in the various long baseline systems in operation around the world – LIGO (USA), Virgo (Italy/France), TAMA300 and LCGT (Japan), and GEO600 (Germany/U.K.) – and in LISA, a proposed space-borne interferometer. A review of recent science runs from the current generation of ground-based detectors will be discussed, in addition to highlighting the astrophysical results gained thus far. Looking to the future, the major upgrades to LIGO (Advanced LIGO), Virgo (Advanced Virgo), LCGT and GEO600 (GEO-HF) will be completed over the coming years, which will create a network of detectors with the significantly improved sensitivity required to detect gravitational waves. Beyond this, the concept and design of possible future “third generation” gravitational-wave detectors, such as the Einstein Telescope (ET), will be discussed.

Physics, Astrophysics and Cosmology with Gravitational Waves

by: B.S. Sathyaprakash and Bernard F. Schutz

Gravitational wave detectors are already operating at interesting sensitivity levels, and they have an upgrade path that should result in secure detections by 2014. We review the physics of gravitational waves, how they interact with detectors (bars and interferometers), and how these detectors operate. We study the most likely sources of gravitational waves and review the data analysis methods that are used to extract their signals from detector noise. Then we consider the consequences of gravitational wave detections and observations for physics, astrophysics, and cosmology.

Gravitational-Wave Data Analysis. Formalism and Sample Applications: The Gaussian Case

by: Piotr Jaranowski and Andrzej Królak

The article reviews the statistical theory of signal detection in application to analysis of deterministic gravitational-wave signals in the noise of a detector. Statistical foundations for the theory of signal detection and parameter estimation are presented. Several tools needed for both theoretical evaluation of the optimal data analysis methods and for their practical implementation are introduced. They include optimal signal-to-noise ratio, Fisher matrix, false alarm and detection probabilities, F-statistic, template placement, and fitting factor. These tools apply to the case of signals buried in a stationary and Gaussian noise. Algorithms to efficiently implement the optimal data analysis techniques are discussed. Formulas are given for a general gravitational-wave signal that includes as special cases most of the deterministic signals of interest.