Accurate characterization of the stochastic gravitational-wave background with pulsar timing arrays by likelihood reweighting

Understand

An isotropic stochastic background of nanohertz gravitational waves creates excess residual power in pulsar-timing-array datasets, with characteristic inter-pulsar correlations described by the Hellings-Downs function.

• These correlations appear as nondiagonal terms in the noise covariance matrix, which must be inverted to obtain the pulsar-timing-array likelihood.
• Searches for the stochastic background, which require many likelihood evaluations, are therefore quite computationally expensive.
• We propose a more efficient method: we first compute approximate posteriors by ignoring cross correlations, and then reweight them to exact posteriors via importance sampling.