Searching for individual supermassive black hole binaries and a stochastic background in population-based simulated pulsar timing array datasets

The dominant source of gravitational waves in the nHz frequency band is expected to be a population of supermassive black hole binaries. The vast majority of these binaries are too weak to be individually detected, however they result in the emergence of a stochastic gravitational wave background. Ongoing pulsar timing array experiments are expected to reach sufficient sensitivities to detect such a stochastic signal within the next few years. As more data is collected, we will also be able to find individual supermassive black hole binaries, which will be excellent sources for multimessenger studies. In terms of detecting the few brightest binaries individually, the gravitational wave background acts as an effective noise source. To study the problem of searching for individual binaries in the presence of a stochastic background, we create a collection of simulated pulsar timing array datasets based on models of the supermassive black hole binary population. We analyze these with a new search technique we have developed, called BayesHopper, which uses trans-dimensional Bayesian inference to allow the model to include an arbitrary number of individual binaries and a stochastic gravitational wave background.