Nanohertz Gravitational Wave Astronomy 1st Edition by Stephen 9781000484786 1000484785

Nanohertz Gravitational Wave Astronomy 1st Edition Stephen R. Taylor – Ebook Instant Download/Delivery ISBN(s): 9781000484786, 1000484785

Product details:

• ISBN 10:1000484785
• ISBN 13:9781000484786
• Author: Stephen 

Nanohertz Gravitational Wave Astronomy

Table contents:

CHAPTER 1 ◾ A Window onto the Warped Universe
CHAPTER 2 ◾ Gravity & Gravitational Waves
2.1 Gravity Before And After Einstein
2.1.1 Standing on the Shoulders of Giants
2.1.2 The Happiest Thought
2.2 Gravitational Waves
2.2.1 A Brief History of Doubt
2.2.2 Waves from Geometry
2.2.2.1 The Quadrupole Formula
2.3 Stochastic Gravitational Wave Backgrounds
2.3.1 The Energy Density of a SGWB
2.3.2 Characteristic Strain
2.3.3 Spectrum of the Strain Signal
2.3.4 Overlap Reduction Function
2.4 The Gravitational Wave Spectrum
2.4.1 Ground-based Detectors
2.4.2 Space-borne Detectors
CHAPTER 3 ◾ Pulsar Timing
3.1 Pulsars
3.2 Precision pulsar timing
3.3 Timing Response To Gravitational Waves
3.4 Overlap Reduction Function For A Background Of Gravitational Waves
CHAPTER 4 ◾ Sources & Signals
4.1 Supermassive binary black holes
4.1.1 Characteristic Strain Spectrum
4.1.2 Binary Dynamical Evolution
4.1.2.1 Dynamical Friction
4.1.2.2 Stellar Loss-cone Scattering
4.1.2.3 Viscous Circumbinary Disk Interaction
4.1.2.4 Gravitational-wave Inspiral
4.1.3 Signal from an Individual Binary
4.1.4 Gravitational-wave Memory Burst
4.2 Exotic gravitational wave sources
4.2.1 Relic GWs
4.2.2 Cosmological Phase Transitions
4.2.3 Cosmic strings
4.3 Non-GW sources of correlated timing delays
4.3.1 Clock errors
4.3.2 Solar-system Ephemeris Errors
4.3.3 Dark Matter
4.3.3.1 Cold dark Matter Substructure
4.3.3.2 Fuzzy Dark Matter
CHAPTER 5 ◾ Data Analysis
5.1 Statistical inference
5.2 Frequentist inference
5.2.1 Significance
5.2.2 Type I & II Errors
5.2.3 Upper Limits
5.3 Bayesian inference
5.3.1 Parameter Estimation
5.3.2 Upper Limits
5.3.3 Model Selection
5.3.3.1 In-sample Model Selection
5.3.3.2 Out-of-Sample Model Selection
CHAPTER 6 ◾ Numerical Bayesian Techniques
6.1 Metropolis algorithms
6.1.1 How Long to Sample?
6.1.2 How to Propose New Parameters?
6.1.2.1 Adaptive Metropolis
6.1.2.2 Single Component Adaptive Metropolis
6.1.2.3 Differential Evolution
6.1.2.4 The Full Proposal Cocktail
6.2 Gibbs sampling
6.3 Evidence evaluation and model selection
6.3.1 Harmonic Mean Estimator
6.3.2 Information Criterion Proxies
6.3.2.1 Bayesian Information Criterion
6.3.2.2 Akaike Information Criterion
6.3.3 Thermodynamic Integration
6.3.4 Nested sampling
6.3.5 Savage-Dickey density ratio
6.3.6 Product Space Sampling
CHAPTER 7 ◾ The PTA Likelihood
7.1 The Pulsar-timing Data Model
7.1.1 Timing Ephemeris
7.1.2 Achromatic Low-frequency Processes
7.1.3 Chromatic Low-frequency Processes
7.1.4 White Noise
7.2 The Likelihood
7.2.1 Full hierarchical Likelihood
7.2.2 Marginalized Likelihood
7.2.3 Modeling Deterministic Signals
7.3 Likelihood-based Statistics
7.3.1 GWB Statistics
7.3.1.1 Optimal Statistic
7.3.1.2 Bridging the Bayesian Odds Ratio and the Frequentist Optimal statistic
7.3.2 Individual Binary Statistics
7.3.2.1 Fe Statistic
7.3.2.2 Fp Statistic
CHAPTER 8 ◾ The Past, Present, and Future of PTAs

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