1. Practical approaches to analyzing PTA data: Cosmic strings with six pulsars
- Author
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Leclere, Hippolyte Quelquejay, Auclair, Pierre, Babak, Stanislav, Chalumeau, Aurélien, Steer, Danièle A., Antoniadis, J., Nielsen, A. -S. Bak, Bassa, C. G., Berthereau, A., Bonetti, M., Bortolas, E., Brook, P. R., Burgay, M., Caballero, R. N., Champion, D. J., Chanlaridis, S., Chen, S., Cognard, I., Desvignes, G., Falxa, M., Ferdman, R. D., Franchini, A., Gair, J. R., Goncharov, B., Graikou, E., Grießmeier, J. -M., Guillemot, L., Guo, Y. J., Hu, H., Iraci, F., Izquierdo-Villalba, D., Jang, J., Jawor, J., Janssen, G. H., Jessner, A., Karuppusamy, R., Keane, E. F., Keith, M. J., Kramer, M., Krishnakumar, M. A., Lackeos, K., Lee, K. J., Liu, K., Liu, Y., Lyne, A. G., McKee, J. W., Main, R. A., Mickaliger, M. B., Niţu, I. C., Parthasarathy, A., Perera, B. B. P., Perrodin, D., Petiteau, A., Porayko, N. K., Possenti, A., Samajdar, A., Sanidas, S. A., Sesana, A., Shaifullah, G., Speri, L., Spiewak, R., Stappers, B. W., Susarla, S. C., Theureau, G., Tiburzi, C., van der Wateren, E., Vecchio, A., Krishnan, V. Venkatraman, Verbiest, J. P. W., Wang, J., Wang, L., Wu, Z., AstroParticule et Cosmologie (APC (UMR_7164)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Centre National d’Études Spatiales [Paris] (CNES), Unité Scientifique de la Station de Nançay (USN), Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherches sur les lois Fondamentales de l'Univers (IRFU), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Laboratoire Univers et Théories (LUTH (UMR_8102)), and EPTA
- Subjects
High Energy Physics - Theory ,kink ,binary: mass ,noise ,data analysis method ,Cosmology and Nongalactic Astrophysics (astro-ph.CO) ,gravitational radiation: stochastic ,string tension ,gravitational radiation: background ,FOS: Physical sciences ,statistical analysis: Bayesian ,General Relativity and Quantum Cosmology (gr-qc) ,parametric ,General Relativity and Quantum Cosmology ,High Energy Physics - Theory (hep-th) ,black hole: binary ,[PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc] ,string: closed ,string model ,simplex ,Astrophysics - Cosmology and Nongalactic Astrophysics ,cosmic string: network ,pulsar - 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 $\log_{10}(Gμ) < -9.9$ ($-10.5$) 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 data sets., 13 pages, 5 figures
- Published
- 2023