Analysis of gravitational-wave data /
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Author / Creator: | Jaranowski, Piotr. |
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Imprint: | Cambridge ; New York : Cambridge University Press, 2009. |
Description: | xii, 257 p. : ill. |
Language: | English |
Series: | Cambridge monographs on particle physics, nuclear physics, and cosmology ; 29 |
Subject: | |
Format: | E-Resource Book |
URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/8209035 |
Table of Contents:
- Preface
- Notation and conventions
- 1. Overview of the theory of gravitational radiation
- 1.1. Linearized general relativity
- 1.2. Plane monochromatic gravitational waves
- 1.3. Description in the TT coordinate system
- 1.4. Description in the observer's proper reference frame
- 1.5. Gravitational waves in the curved background
- 1.6. Energy-momentum tensor for gravitational waves
- 1.7. Generation of gravitational waves and radiation reaction
- 2. Astrophysical sources of gravitational waves
- 2.1. Burst sources
- 2.2. Periodic sources
- 2.3. Stochastic sources
- 2.4. Case study: binary systems
- 2.5. Case study: a rotating triaxial ellipsoid
- 2.6. Case study: supernova explosion
- 2.7. Case study: stochastic background
- 3. Statistical theory of signal detection
- 3.1. Random variables
- 3.2. Stochastic processes
- 3.3. Hypothesis testing
- 3.4. The matched filter in Gaussian noise: deterministic signal
- 3.5. Estimation of stochastic signals
- 3.6. Estimation of parameters
- 3.7. Non-stationary stochastic processes
- 4. Time series analysis
- 4.1. Sample mean and correlation function
- 4.2. Power spectrum estimation
- 4.3. Tests for periodicity
- 4.4. Goodness-of-fit tests
- 4.5. Higher-order spectra
- 5. Responses of detectors to gravitational waves
- 5.1. Detectors of gravitational waves
- 5.2. Doppler shift between freely falling observers
- 5.3. Long-wavelength approximation
- 5.4. Responses of the solar-system-based detectors
- 6. Maximum-likelihood detection in Gaussian noise
- 6.1. Deterministic signals
- 6.2. Case studies: deterministic signals
- 6.3. Network of detectors
- 6.4. Detection of stochastic signals
- 7. Data analysis tools
- 7.1. Linear signal model
- 7.2. Grid of templates in the parameter space
- 7.3. Numerical algorithms to calculate the F-statistic
- 7.4. Analysis of the candidates
- Appendix A. The chirp waveform
- Appendix B. Proof of the Neyman-Pearson lemma
- Appendix C. Detector's beam-pattern functions
- C.1. LISA detector
- C.2. Earth-based detectors
- Appendix D. Response of the LISA detector to an almost monochromatic wave
- Appendix E. Amplitude parameters of periodic waves
- References
- Index