Rapid & Flexible Gravitational-wave Background Characterization With Pulsar Timing Arrays

Nanohertz-frequency gravitational waves (GW) are expected from various astrophysical and cosmological sources, such as supermassive black-hole binaries, cosmic strings, and cosmological phase transitions. They can be detected by Pulsar Timing Arrays (PTAs), which search for GW-induced deviations between the expected and observed times-of-arrivals (TOAs) of radio pulses in many pulsars. Using Bayesian inference, we conduct our analysis by fitting GW models from various GW sources to PTA timing residuals. Current techniques are cumbersome, with each analysis taking days or even weeks. As PTAs collect more data from more pulsars, current analysis timescales will only slow down. In this talk, I will introduce the Generalised Factorised Likelihood (GFL) method and how it will revolutionise PTA analyses. It is a fast and flexible Bayesian technique to compress and analyse PTA data, accurately characterising the spectral properties from various GW phenomena to place limits on GW models, all while decreasing analysis times to just a few minutes.