Pulsar Timing Arrays require hierarchical models

Abstract

Pulsar Timing Array projects have found evidence of a stochastic background of gravitational waves (GWB) using data from an ensemble of pulsars. In the literature, minimal assumptions are made about the signal and noise processes that affect data from these pulsars, such as pulsar spin noise. These assumptions are encoded as uninformative priors in Bayesian searches, though Frequentist approaches make similar assumptions. Uninformative priors are not suitable for (noise) properties of pulsars in an ensemble, and they bias estimates of model parameters such as gravitational-wave signal parameters. Both Frequentist and Bayesian searches are affected. In this letter, more appropriate priors are proposed in the language of Hierarchical Bayesian Modeling, where the properties of the ensemble of pulsars are jointly described with the properties of the individual components of the ensemble. Results by Pulsar Timing Array projects should be re-evaluated using Hierarchical Models.

16 pages, 9 figures, accepted for publication in ApJS

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• Ensemble noise properties of the European Pulsar Timing Array
• Reading signatures of supermassive binary black holes in pulsar timing array observations
• Choosing suitable noise models for nanohertz gravitational-wave astrophysics
• Rapid Construction of Joint Pulsar Timing Array Datasets: The Lite Method
• The NANOGrav 15 yr Data Set: Customized Chromatic Noise Models
• On the calculation of p-values for quadratic statistics in Pulsar Timing Arrays
• Gravitational-wave astronomy requires population-informed parameter estimation
• Measuring the crust-superfluid coupling time-scale for 105 UTMOST pulsars with a Kalman filter