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Abstract: Long-term precise timing of Galactic millisecond pulsars holds great promisefor measuring the long-period months-to-years astrophysical gravitationalwaves. Several gravitational-wave observational programs, called Pulsar TimingArrays PTA, are being pursued around the world. Here we develop a Bayesianalgorithm for measuring the stochastic gravitational-wave background GWB fromthe PTA data. Our algorithm has several strengths: 1 It analyses the datawithout any loss of information, 2 It trivially removes systematic errors ofknown functional form, including quadratic pulsar spin-down, annual modulationsand jumps due to a change of equipment, 3 It measures simultaneously both theamplitude and the slope of the GWB spectrum, 4 It can deal with unevenlysampled data and coloured pulsar noise spectra. We sample the likelihoodfunction using Markov Chain Monte Carlo MCMC simulations. We extensively testour approach on mock PTA datasets, and find that the algorithm has significantbenefits over currently proposed counterparts. We show the importance ofcharacterising all red noise components in pulsar timing noise by demonstratingthat the presence of a red component would significantly hinder a detection ofthe GWB. Lastly, we explore the dependence of the signal-to-noise ratio on theduration of the experiment, number of monitored pulsars, and the magnitude ofthe pulsar timing noise. These parameter studies will help formulate observingstrategies for the PTA experiments.



Author: Rutger van Haasteren, Yuri Levin, Patrick McDonald, Tingting Lu

Source: https://arxiv.org/







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