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Intro
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Classroom Contents
Gravitational Wave Parameter Estimation with Compressed Likelihood Evaluations
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- 1 Intro
- 2 Gravitational wave datasets
- 3 Bayesian inference of GW datasets
- 4 Likelhood computations are too slow
- 5 Parameter estimation challenges
- 6 Approaches to faster PE (non-exhausthe list)
- 7 Reduced order quadratures (ROQS) in use
- 8 Outline
- 9 Numerical integration (quadrature)
- 10 Do I need a low-order quadrature rule for noisy data?
- 11 Probler Formulation
- 12 Step 1: Compressing the model
- 13 Best approximation space X
- 14 Example basis generation
- 15 Waveform compression application (ex: 1.2040)
- 16 Summary of step 1
- 17 Where are the good points for integrating in X.?
- 18 Empirical interpolation method
- 19 Example: Points for polynomial interpolation integratior
- 20 The ROQ approximation
- 21 Using ROQ
- 22 Building ROQ
- 23 Startup a signal has been detected!
- 24 How much faster?
- 25 Accelerating tests of GR
- 26 BNS events with third generation observatories
