Literature DB >> 28163647

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

Piotr Jaranowski1, Andrzej Królak2.   

Abstract

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, [Formula: see text]-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.

Entities:  

Year:  2005        PMID: 28163647      PMCID: PMC5253919          DOI: 10.12942/lrr-2005-3

Source DB:  PubMed          Journal:  Living Rev Relativ        ISSN: 1433-8351            Impact factor:   40.429


  19 in total

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Journal:  Phys Rev D Part Fields       Date:  1992-12-15

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Journal:  Phys Rev D Part Fields       Date:  1993-04-15

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Journal:  Phys Rev D Part Fields       Date:  1989-12-15

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Journal:  Phys Rev D Part Fields       Date:  1994-03-15

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Journal:  Phys Rev D Part Fields       Date:  1994-02-15

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Journal:  Phys Rev D Part Fields       Date:  1993-10-15

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Journal:  Phys Rev D Part Fields       Date:  1994-02-15

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Journal:  Phys Rev D Part Fields       Date:  1993-01-15

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Journal:  Phys Rev D Part Fields       Date:  1993-03-15

10.  Choice of filters for the detection of gravitational waves from coalescing binaries.

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Journal:  Phys Rev D Part Fields       Date:  1991-12-15
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  1 in total

1.  A template-free approach for waveform extraction of gravitational wave events.

Authors:  A Akhshi; H Alimohammadi; S Baghram; S Rahvar; M Reza Rahimi Tabar; H Arfaei
Journal:  Sci Rep       Date:  2021-10-15       Impact factor: 4.379

  1 in total

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