Weighing The Evidence For A Gravitational-Wave Background In The First International Pulsar Timing Array Data Challenge

TL;DR

This paper analyzes the first International Pulsar Timing Array Data Challenge using Bayesian methods, detecting a gravitational-wave background consistent with supermassive black-hole binaries and evaluating the impact of data down-sampling.

Contribution

It applies a robust Bayesian framework to analyze pulsar timing data, providing evidence for gravitational-wave backgrounds and assessing data processing effects.

Findings

Favored a gravitational-wave background with specific amplitude and spectral index in datasets Closed1 and Closed2.

Detected red-timing noise and gravitational-wave background in dataset Closed3.

Confirmed the background's properties are consistent with inspiraling supermassive black-hole binaries.

Abstract

We describe an analysis of the First International Pulsar Timing Array Data Challenge. We employ a robust, unbiased Bayesian framework developed by van Haasteren to study the three Open and Closed datasets, testing various models for each dataset and using MultiNest to recover the evidence for the purposes of Bayesian model-selection. The parameter constraints of the favoured model are confirmed using an adaptive MCMC technique. Our results for Closed1 favoured a gravitational-wave background with strain amplitude at f=1 yr-1, A, of (1.1 +/- 0.1) x 10^{-14}, power spectral-index gamma=4.30 +/- 0.15 and no evidence for red-timing noise or single-sources. The evidence for Closed2 favours a gravitational-wave background with A=(6.1 +/- 0.3) x 10^{-14}, gamma=4.34 +/- 0.09 with no red-timing noise or single-sources. Finally, the evidence for Closed3 favours the presence of red-timing noise and a gravitational-wave background, with no single-sources. The properties of the background were A=(5 +/- 1) x 10^{-15} and gamma=4.23 +/- 0.35, while the properties of the red-noise were N_{red}=(12 +/- 4) ns and gamma_{red}=1.5 +/- 0.3. In all cases the redness of the recovered background is consistent with a source-population of inspiraling supermassive black-hole binaries. We also investigate the effect that down-sampling of the datasets has on parameter constraints and run-time. Finally we provide a proof-of-principle study of the ability of the Bayesian framework used in this paper to reconstruct the angular correlation of gravitational-wave background induced timing-residuals, comparing this to the Hellings and Downs curve.