Bayley, J. , Messenger, C. and Woan, G. (2022) Rapid parameter estimation for an all-sky continuous gravitational wave search using conditional varitational auto-encoders. Physical Review D, 106(8), 083022. (doi: 10.1103/PhysRevD.106.083022)
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Abstract
All-sky searches for continuous gravitational waves are generally model dependent and computationally costly to run. By contrast, SOAP is a model-agnostic search that rapidly returns candidate signal tracks in the time-frequency plane. In this work, we extend the SOAP search to return broad Bayesian posteriors on the astrophysical parameters of a specific signal model. These constraints drastically reduce the volume of parameter space that any follow-up search needs to explore, so increasing the speed at which candidates can be identified and confirmed. Our method uses a machine learning technique, specifically a conditional variational auto-encoder, and delivers a rapid estimation of the posterior distribution of the four Doppler parameters of a continuous wave signal. It does so without requiring a clear definition of a likelihood function or being shown any true Bayesian posteriors in training. We demonstrate how the Doppler parameter space volume can be reduced by a factor of O(10−7) for signals of SNR 100.
| Item Type: | Articles |
|---|---|
| Additional Information: | This research is supported by the Science and Technology Facilities Council. J. B., G. W., and C. M. are supported by the Science and Technology Research Council (Grant No. ST/V005634/1). C. M. is also supported by the European Cooperation in Science and Technology (COST) action CA17137. The authors are grateful for computational resources provided by the LIGO Laboratory supported by National Science Foundation Grants No. PHY-0757058 and No. PHY-0823459. |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Messenger, Dr Christopher and Woan, Professor Graham and Bayley, Mr Joseph |
| Authors: | Bayley, J., Messenger, C., and Woan, G. |
| College/School: | College of Science and Engineering > School of Physics and Astronomy |
| Research Centre: | College of Science and Engineering > School of Physics and Astronomy > Institute for Gravitational Research |
| Journal Name: | Physical Review D |
| Publisher: | American Physical Society |
| ISSN: | 2470-0010 |
| ISSN (Online): | 2470-0029 |
| Published Online: | 26 October 2022 |
| Copyright Holders: | Copyright © 2022 American Physical Society |
| First Published: | First published in Physical Review D 8:083022 |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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