Looking for non-gaussianity in Pulsar Timing Arrays through the four point correlator

TL;DR

This paper develops a theoretical framework to detect non-gaussian features in the stochastic gravitational wave background using four-point correlators in pulsar timing array data, extending beyond standard gaussian assumptions.

Contribution

It introduces the complete four-point correlator for pulsar timing arrays, identifying non-gaussian signals and proposing a likelihood method to incorporate these effects into data analysis.

Findings

Derived the four-point correlator for arbitrary pulsar positions.

Separated gaussian and non-gaussian contributions with angular dependence.

Proposed a likelihood method to include non-gaussianity in parameter estimation.

Abstract

Pulsar Timing Arrays have recently reported strong evidence for a stochastic gravitational wave background. In standard analyses, it is modeled through pulsar-dependent Fourier coefficients assumed to follow gaussian statistics, so that the signal is fully characterized by its two-point function. However, if the background arises from a finite population of inspiralling supermassive black hole binaries, non-gaussian features may emerge, making the determination of higher-order correlators essential. In this work, we compute the complete four-point correlator of the stochastic gravitational wave background Fourier coefficients for four arbitrary pulsar positions, identifying it as the leading probe of non-gaussianity. The result separates into a gaussian contribution, proportional to the square of the two-point function, and a genuinely non-gaussian connected component, whose non-trivial angular dependence generalizes the Hellings and Downs correlation to four pulsars. This angular structure depends only on averages of products of antenna pattern functions, and is therefore expected to be independent of the specific physical origin of the background. We further propose to incorporate the four-point correlator into the parameter-estimation pipeline by deriving a marginalized likelihood that perturbatively accounts for non-gaussian effects. Our results provide the theoretical framework to search for non-gaussian features in pulsar timing array data, opening the way to a more complete characterization of gravitational-wave backgrounds.