Abstract
We search for a stochastic gravitational wave background (SGWB) generated by a network of cosmic strings using six millisecond pulsars from Data Release 2 (DR2) of the European Pulsar Timing Array (EPTA). We perform a Bayesian analysis considering two models for the network of cosmic string loops, and compare it to a simple power-law model which is expected from the population of supermassive black hole binaries. Our main strong assumption is that the previously reported common red noise process is a SGWB. We find that the one-parameter cosmic string model is slightly favored over a power-law model thanks to its simplicity. If we assume a two-component stochastic signal in the data (supermassive black hole binary population and the signal from cosmic strings), we get a 95% upper limit on the string tension of log10(G μ )<-9.9 (-10.5 ) for the two cosmic string models we consider. In extended two-parameter string models, we were unable to constrain the number of kinks. We test two approximate and fast Bayesian data analysis methods against the most rigorous analysis and find consistent results. These two fast and efficient methods are applicable to all SGWBs, independent of their source, and will be crucial for analysis of extended datasets.
Original language | English |
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Article number | 123527 |
Number of pages | 14 |
Journal | Physical Review D (Particles, Fields, Gravitation and Cosmology) |
Volume | 108 |
Issue number | 12 |
DOIs | |
Publication status | Published - 15 Dec 2023 |
Bibliographical note
ACKNOWLEDGMENTSH. Q.-L., P. A., and D. S. would like to thank the University of Geneva for hospitality while this work was in progress. We are grateful to Chiara Caprini for very useful discussions. H. Q.-L. thanks Institut Polytechnique de Paris for funding his PhD. The work of P. A. is supported by the Wallonia-Brussels Federation Grant ARC No 19/24-103. S. B. and H. Q.-L. acknowledge support from ANR-21-CE31-0026, project MBH_waves. D. S. is grateful to CERN for hospitality.