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== General ==

 * "Maggiore M-Gravitational waves vol.1 Theory and Experiments-Oxford University Press (2008)" for [Data analysis and theory]
  *http://gwwiki.icrr.u-tokyo.ac.jp/JGWwiki/KAGRA/KSC/EducationTraining/ReadingMaterials/DATheory

 * Jolien D. E. Creighton and Warren G. Anderson. Gravitational-Wave Physics and Astronomy. (Wiley-VCH)

== General(data analysis) ==

 * Andrés Asensio Ramos and Íñigo Arregui. Bayesian Astrophysics. (Canary Islands Winter School of Astrophysics Book 26)
 
 * Sophocles J. Orfanidis. Introduction to Signal Processing. (Prentice Hall)

 * An introduction to Bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models. Publications of the Astronomical Society of Australia (2019), 36, e010, 12 pages doi:10.1017/pasa.2019.2

Introductory reading materials for GW data analysis and theory

Contents

  1. Introductory reading materials for GW data analysis and theory
    1. General
    2. General(data analysis)
    3. General Relativity
      1. Numerical relativity
    4. CBC
    5. Unmodeled burst
    6. Continuous
    7. Stochastic

General

General(data analysis)

  • Andrés Asensio Ramos and Íñigo Arregui. Bayesian Astrophysics. (Canary Islands Winter School of Astrophysics Book 26)
  • Sophocles J. Orfanidis. Introduction to Signal Processing. (Prentice Hall)
  • An introduction to Bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models. Publications of the Astronomical Society of Australia (2019), 36, e010, 12 pages doi:10.1017/pasa.2019.2

General Relativity

Numerical relativity

CBC

Unmodeled burst

Continuous

Stochastic

KAGRA/KSC/EducationTraining/ReadingMaterials/DATheory (last edited 2021-05-01 22:05:48 by KazuhiroYamamoto)