Leveraging rapid parameter estimates for efficient gravitational-wave Bayesian inference via posterior repartitioning

TL;DR

This paper introduces a new method combining rapid parameter estimation with posterior repartitioning to accelerate Bayesian inference in gravitational wave analysis, maintaining statistical rigor and unbiased results.

Contribution

The authors develop a novel approach that leverages quick low-latency estimates to guide nested sampling, significantly speeding up analysis without compromising accuracy.

Findings

Speedups of up to 2.2 times for signals with SNR less than 150.

Method guides nested sampling more efficiently at higher SNRs.

Final inference remains identical to standard analysis, ensuring statistical validity.

Abstract

Gravitational wave astronomy typically relies on rigorous, computationally expensive Bayesian analyses. Several methods have been developed to perform rapid Bayesian inference, but they are not yet used to inform our full analyses. We present a novel approach for doing this whilst ensuring that the Bayesian prior remains independent of the data, providing a statistically rigorous way to leverage low-latency information to accelerate the final inference. By combining the fast constraints from the simple-pe algorithm with the nested sampling acceleration technique of posterior repartitioning, we demonstrate that our method can guide the nested sampler towards the most probable regions of parameter space more efficiently for signal-to-noise ratios (SNR) greater than 20, while mathematically guaranteeing that the final inference is identical to that of a standard, uninformed analysis. We validate the method through an injection study, demonstrating that it produces statistically robust and unbiased results, whilst providing speedups of up to $2.2\times$ for binaries with SNRs $< 150$. Importantly, we show that the performance gain provided by our method scales with SNR, establishing it as a powerful technique to mitigate the cost of analysing signals from current and future gravitational-wave observatories.