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Bayesian inference for compact binary sources of gravitational waves

Abstract : The first detection of gravitational waves in 2015 has opened a new window for the study of the astrophysics of compact binaries. Thanks to the data taken by the ground-based detectors advanced LIGO and advanced Virgo, it is now possible to constrain the physical parameters of compact binaries using a full Bayesian analysis in order to increase our physical knowledge on compact binaries. However, in order to be able to perform such analysis, it is essential to have efficient algorithms both to search for the signals and for parameter estimation. The main part of this thesis has been dedicated to the implementation of a Hamiltonian Monte Carlo algorithm suited for the parameter estimation of gravitational waves emitted by compact binaries composed of neutron stars. The algorithm has been tested on a selection of sources and has been able to produce better performances than other types of MCMC methods such as Metropolis-Hastings and Differential Evolution Monte Carlo. The implementation of the HMC algorithm in the data analysis pipelines of the Ligo/Virgo collaboration could greatly increase the efficiency of parameter estimation. In addition, it could also drastically reduce the computation time associated to the parameter estimation of such sources of gravitational waves, which will be of particular interest in the near future when there will many detections by the ground-based network of gravitational wave detectors. Another aspect of this work was dedicated to the implementation of a search algorithm for gravitational wave signals emitted by monochromatic compact binaries as observed by the space-based detector LISA. The developed algorithm is a mixture of several evolutionary algorithms, including Particle Swarm Optimisation. This algorithm has been tested on several test cases and has been able to find all the sources buried in a signal. Furthermore, the algorithm has been able to find the sources on a band of frequency as large as 1 mHz which wasn’t done at the time of this thesis study
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Submitted on : Tuesday, April 16, 2019 - 7:43:07 PM
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Yann Bouffanais. Bayesian inference for compact binary sources of gravitational waves. Physics [physics]. Université Sorbonne Paris Cité, 2017. English. ⟨NNT : 2017USPCC197⟩. ⟨tel-02101561⟩



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