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07:46
Setting Limits on Supersymmetry Using Simplified Models
Published on: November 15, 2013
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Novel method for incorporating model uncertainties into gravitational wave parameter estimates.
Christopher J Moore1, Jonathan R Gair1
1Institute of Astronomy, Madingley Road, Cambridge CB30HA, United Kingdom.
Physical Review Letters
|January 3, 2015
Summary
This study introduces a new Bayesian data analysis method to account for model uncertainties. It improves parameter estimation accuracy in fields like gravitational wave detection by interpolating waveform differences using Gaussian process regression.
Area of Science:
- Computational Physics
- Statistical Inference
- Astrophysics
Background:
- Bayesian inference accuracy depends on model completeness; incomplete models introduce systematic errors.
- Gravitational wave data analysis requires accurate waveform templates, but simulations are computationally expensive.
- Existing methods struggle to incorporate uncertainties from incomplete waveform models.
Purpose of the Study:
- To propose a novel method for incorporating model uncertainties into Bayesian data analysis.
- To improve the accuracy of parameter estimation in the presence of model deficiencies.
- To develop a computationally efficient technique applicable to gravitational wave data analysis and beyond.
Main Methods:
- Developed a method to analytically marginalize waveform uncertainties.
- Constructed a prior distribution using Gaussian process regression.
- Interpolated waveform differences from a small set of accurate templates.
Main Results:
- The proposed method effectively folds model uncertainties into data analysis.
- Demonstrated excellent performance on a toy problem.
- The technique is computationally efficient and easy to implement.
Conclusions:
- The novel method successfully addresses the challenge of model incompleteness in Bayesian analysis.
- Applicable to gravitational wave detection and any field with model uncertainties.
- Offers a practical solution for enhancing parameter estimation accuracy.
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