Approximating the statistics of a gravitational wave background

Abstract

The astrophysical origin of the gravitational wave background (GWB) reported by pulsar timing array (PTA) collaborations has yet to be confirmed. A GWB signal made of the sum of individual gravitational wave (GW) from the population of supermassive black hole binaries (SMBHB) would show the imprint of a discrete Poissonian statistics in its spectral properties. In this work, we propose a tool based on the saddlepoint approximation method to estimate the distribution of characteristic strain for any given population model. This tool can be used for Bayesian inference or for a quick visualization of the statistics of the GWB from the output of more realistic semi-analytical models. We introduce the general family of variance mixture Gaussian distributions that models heavy-tailed behavior distributions that is expected for a non-Gaussian GWB signal. We show that setting the correct hierarchical priors to a Gaussian free spectrum PTA likelihood is effectively equivalent to a non-Gaussian likelihood. Using ideal simulations, we compare the performance of the saddlepoint approximation with a log-Normal distribution to infer the parameters of the astrophysical model from the statistics of the GWB and show that correctly modeling higher order moments is essential. Future PTA analyses should include the statistics of the GWB in their pipelines.