Abstract

It is fair to say that the first direct detection of gravitational waves is one of the most sought after goals in science today. Here we present a new method for analysing data from a pulsar timing array – a collection of Galactic millisecond pulsars – from which the signal induced by a stochastic gravitational wave background (GWB) could be extracted. Existing Bayesian methods for such analysis are for the most part extremely computationally expensive, and assume power-law models for the shape of the GWB spectrum. Our method eliminates the most costly aspects of computation associated with this type of analysis, resulting in a decrease in run-time from days to minutes, and critically at no stage requires the need to specify any prior form for the shape of the GWB power spectrum. Our method of sampling also allows us to include parameterisation of the spatial correlations between pulsars directly. The shape of this correlation is the ‘smoking gun’ of a signal from a GWB , and so the ability to extract it from the data without assuming its presence is crucial for the credibility of any future detection, and, in short makes this the only Bayesian, model-independent method for performing this sort of analysis currently available.