Projects per year
Abstract
Once upon a time, predictions for the accuracy of inference on gravitational-wave signals relied on computationally inexpensive but often imprecise techniques. Recently, the approach has shifted to actual inference on noisy signals with complex stochastic Bayesian methods, at the expense of significant computational cost. Here, we argue that it is often possible to have the best of both worlds: a Bayesian approach that incorporates prior information and correctly marginalizes over uninteresting parameters, providing accurate posterior probability distribution functions, but carried out on a simple grid at a low computational cost, comparable to the inexpensive predictive techniques.
Original language | English |
---|---|
Article number | 235017 |
Journal | Classical and Quantum Gravity |
Volume | 32 |
Issue number | 23 |
DOIs | |
Publication status | Published - 13 Nov 2015 |
Keywords
- data analysis
- gravitational waves
- parameter estimation
ASJC Scopus subject areas
- Physics and Astronomy (miscellaneous)
Fingerprint
Dive into the research topics of 'Efficient method for measuring the parameters encoded in a gravitational-wave signal'. Together they form a unique fingerprint.Projects
- 3 Finished
-
Birmingham Astrophysics : Consolidated Grant 2013-2016
Vecchio, A., Ponman, T., Freise, A., Smith, G., Speake, C., Mandel, I., Cruise, M., Raychaudhury, S. & Stevens, I.
SCIENCE & TECHNOLOGY FACILITIES COUNCIL
1/04/13 → 30/09/16
Project: Research Councils
-
UK Involvement in the Operations of Advanced LIGO
Vecchio, A. & Freise, A.
SCIENCE & TECHNOLOGY FACILITIES COUNCIL
1/08/11 → 31/12/15
Project: Research Councils
-
UK Involvement in the Advanced LIGO Gravitational Wave Project
Vecchio, A., Castelli, C. & Cruise, M.
SCIENCE & TECHNOLOGY FACILITIES COUNCIL
1/06/03 → 31/03/11
Project: Research Councils