The NANOGrav 15 yr dataset: Posterior predictive checks for gravitational-wave detection with pulsar timing arrays

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Abstract

Pulsar timing array experiments have reported evidence for a stochastic background of nanohertz gravitational waves consistent with the signal expected from a population of supermassive black hole binaries. Their analyses assume power-law spectra for intrinsic pulsar noise and for the background, as well as a Hellings-Downs cross-correlation pattern among the gravitational-wave-induced residuals across pulsars. These assumptions may not be realized in actuality. We test them in the NANOGrav 15 yr dataset using Bayesian posterior predictive checks. After fitting our fiducial model to real data, we generate a population of simulated dataset replications. We use the replications to assess whether the optimal statistic significance, interpulsar correlations, and spectral coefficients are extreme. We recover Hellings-Downs correlations in simulated datasets at significance levels consistent with the correlations measured in the NANOGrav 15 yr dataset. A similar test on spectral coefficients shows that their values in real data are not extreme compared to their distributions across replications. We also evaluate the evidence for the stochastic background using posterior predictive versions of the frequentist optimal statistic and of Bayesian model comparison and find comparable significance ($3.2\ensuremath{\sigma}$ and $3\ensuremath{\sigma}$ respectively) to what was previously reported for the standard statistics. We conclude with novel visualizations of the reconstructed gravitational waveforms that enter the residuals for each pulsar. Our analysis strengthens confidence in the identification and characterization of the gravitational-wave background.

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