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Disentangling Multiple Stochastic Gravitational Wave Background Sources in PTA Data Sets

Andrew R. Kaiser, Nihan S. Pol, M. A. McLaughlin, Siyuan Chen, Jeffrey S. Hazboun, Luke Zoltan Kelley, Joseph Simon, Stephen R. Taylor, Sarah J. Vigeland, Caitlin A. Witt

2022The Astrophysical Journal19 citationsDOIOpen Access PDF

Abstract

Abstract With strong evidence of a common-spectrum stochastic process in the most recent data sets from the NANOGrav Collaboration, the European Pulsar Timing Array (PTA), Parkes PTA, and the International PTA, it is crucial to assess the effects of the several astrophysical and cosmological sources that could contribute to the stochastic gravitational wave background (GWB). Using the same data set creation and injection techniques as in Pol et al., we assess the separability of multiple GWBs by creating single and multiple GWB source data sets. We search for these injected sources using Bayesian PTA analysis techniques to assess recovery and separability of multiple astrophysical and cosmological backgrounds. For a GWB due to supermassive black hole binaries and an underlying weaker background due to primordial gravitational waves with a GW energy-density ratio of Ω PGW /Ω SMBHB = 0.5, the Bayes’ factor for a second process exceeds unity at 17 yr, and increases with additional data. At 20 yr of data, we are able to constrain the spectral index and amplitude of the weaker GWB at this density ratio to a fractional uncertainty of 64% and 110%, respectively, using current PTA methods and techniques. Using these methods and findings, we outline a basic protocol to search for multiple backgrounds in future PTA data sets.

Topics & Concepts

PhysicsGravitational waveGravitational wave backgroundBayes factorAstrophysicsPulsarAmplitudeData setSupermassive black holeBayesian probabilityBayesian inferenceStatisticsQuantum mechanicsGalaxyMathematicsCosmology and Gravitation TheoriesPulsars and Gravitational Waves ResearchRadio Astronomy Observations and Technology
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