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Principles of Gravitational-Wave DataAnalysis

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Handbook of Gravitational Wave Astronomy
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Abstract

Basic mathematical concepts of gravitational-wave data analysis are introduced. In particular statistical principles of detection of signals in noise and estimation of their parameters are presented. Applications to the main signals of gravitational waves that can be modeled as functions of time dependent on several unknown parameters are given.

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References

  1. Jaranowski P, Królak A (2005) Gravitational-wave data analysis. Formalism and sample applications: the Gaussian case. Living Rev Relativ 8:3

    Google Scholar 

  2. Jaranowski P, Królak A (2009) Analysis of gravitational-wave data. Cambridge University Press, Cambridge

    Book  Google Scholar 

  3. Bayes T (1763) An essay towards solving a problem in doctrine of chances. Phil Trans R Soc 53:293–315

    MathSciNet  MATH  Google Scholar 

  4. Neyman J, Pearson E (1933) On the problem of the most efficient tests of statistical hypothesis. Phil Trans R Soc Ser A 231:289–337

    ADS  MATH  Google Scholar 

  5. Wald A (1939) Contribution to the theory of statistical estimation and testing of hypotheses. Ann Math Stat 10:299–326

    Article  MathSciNet  Google Scholar 

  6. Rao C (1945) Information and the accuracy attainable in the estimation of statistical parameters. Bull Calcutta Math Soc 37:81–89

    MathSciNet  MATH  Google Scholar 

  7. Cramèr H (1946) Mathematical methods of statistic. Princeton University Press, Princeton

    MATH  Google Scholar 

  8. Wilks SS (1938) The large-sample distribution of the likelihood ratio for testing composite hypotheses. Ann Math Stat 9:60

    Article  Google Scholar 

  9. Adler J (1981) The geometry of random fields. Wiley, New York

    MATH  Google Scholar 

  10. Jaranowski P, Królak A, Schutz BF (1998) Data analysis of gravitational-wave signals from spinning neutron stars: the signal and its detection. Phys Rev D58:063001

    ADS  Google Scholar 

  11. Owen BJ (1996) Search templates for gravitational waves from inspiraling binaries: choice of template spacing. Phys Rev D53:6749–6761

    ADS  Google Scholar 

  12. Meyer C (2000) Matrix analysis and applied linear algebra. SIAM, Philadelphia

    Book  Google Scholar 

  13. Apostolatos TA (1995) Search templates for gravitational waves from precessing, inspiraling binaries. Phys Rev D52:605–620

    ADS  Google Scholar 

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Acknowledgements

The work was supported in part by the Polish National Science Centre grant no. 2017/26/M/ST9/00978.

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Correspondence to Andrzej Królak .

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Królak, A. (2022). Principles of Gravitational-Wave DataAnalysis. In: Bambi, C., Katsanevas, S., Kokkotas, K.D. (eds) Handbook of Gravitational Wave Astronomy. Springer, Singapore. https://doi.org/10.1007/978-981-16-4306-4_43

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