Details
| Original language | English |
|---|---|
| Article number | 103020 |
| Journal | Physical Review D |
| Volume | 97 |
| Issue number | 10 |
| Publication status | Published - 15 May 2018 |
Abstract
Leveraging Markov chain Monte Carlo optimization of the F statistic, we introduce a method for the hierarchical follow-up of continuous gravitational wave candidates identified by wide-parameter space semicoherent searches. We demonstrate parameter estimation for continuous wave sources and develop a framework and tools to understand and control the effective size of the parameter space, critical to the success of the method. Monte Carlo tests of simulated signals in noise demonstrate that this method is close to the theoretical optimal performance.
ASJC Scopus subject areas
- Physics and Astronomy(all)
- Physics and Astronomy (miscellaneous)
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In: Physical Review D, Vol. 97, No. 10, 103020, 15.05.2018.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Hierarchical multistage MCMC follow-up of continuous gravitational wave candidates
AU - Ashton, G.
AU - Prix, R.
N1 - Publisher Copyright: © 2018 American Physical Society.
PY - 2018/5/15
Y1 - 2018/5/15
N2 - Leveraging Markov chain Monte Carlo optimization of the F statistic, we introduce a method for the hierarchical follow-up of continuous gravitational wave candidates identified by wide-parameter space semicoherent searches. We demonstrate parameter estimation for continuous wave sources and develop a framework and tools to understand and control the effective size of the parameter space, critical to the success of the method. Monte Carlo tests of simulated signals in noise demonstrate that this method is close to the theoretical optimal performance.
AB - Leveraging Markov chain Monte Carlo optimization of the F statistic, we introduce a method for the hierarchical follow-up of continuous gravitational wave candidates identified by wide-parameter space semicoherent searches. We demonstrate parameter estimation for continuous wave sources and develop a framework and tools to understand and control the effective size of the parameter space, critical to the success of the method. Monte Carlo tests of simulated signals in noise demonstrate that this method is close to the theoretical optimal performance.
UR - http://www.scopus.com/inward/record.url?scp=85048087811&partnerID=8YFLogxK
U2 - 10.1103/PhysRevD.97.103020
DO - 10.1103/PhysRevD.97.103020
M3 - Article
AN - SCOPUS:85048087811
VL - 97
JO - Physical Review D
JF - Physical Review D
SN - 2470-0010
IS - 10
M1 - 103020
ER -