Accelerated Bayesian model-selection and parameter-estimation in   continuous gravitational-wave searches with pulsar-timing arrays
  We describe several new techniques which accelerate Bayesian searches for continuous gravitational-wave emission from supermassive black-hole binaries using pulsar timing arrays. These techniques mitigate the problematic increase of search-dimensionality with the size of the pulsar array which arises from having to include an extra parameter per pulsar as the array is expanded. This extra parameter corresponds to searching over the phase of the gravitational-wave as it propagates past each pulsar so that we can coherently include the pulsar-term in our search strategies. Our techniques make the analysis tractable with powerful evidence-evaluation packages like MultiNest. We find good agreement of our techniques with the parameter-estimation and Bayes factor evaluation performed with full signal templates, and conclude that these techniques make excellent first-cut tools for detection and characterisation of continuous gravitational-wave signals with pulsar timing arrays. Crucially, at low to moderate signal-to-noise ratios the factor by which the analysis is sped up can be > 100, permitting rigorous programs of systematic injection and recovery of signals to establish robust detection criteria within a Bayesian formalism. 
Stephen Taylor, Justin Ellis, Jonathan Gair
gr-qc astro-ph.HE astro-ph.IM