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2023

Fast Parameter Inference on Pulsar Timing Arrays with Normalizing Flows

Shih, David, Freytsis, Marat, Taylor, Stephen R. et al.

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Pulsar timing arrays (PTAs) perform Bayesian posterior inference with expensive MCMC methods.

Given a dataset of ~10-100 pulsars and O(10^3) timing residuals each, producing a posterior distribution for the stochastic gravitational wave background (SGWB) can take days to a week.
The computational bottleneck arises because the likelihood evaluation required for MCMC is extremely costly when considering the dimensionality of the search space.
Fortunately, generating simulated data is fast, so modern simulation-based inference techniques can be brought to bear on the problem.

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