Analytic weak-signal approximation of the Bayes factor for continuous gravitational waves
Reinhard Prix

TL;DR
This paper introduces a new analytic approximation for the Bayes factor in continuous gravitational wave searches, improving computational efficiency and robustness across various segment lengths.
Contribution
It generalizes the targeted $ ext{B}$-statistic with a half-Gaussian prior, enabling fully analytic marginalization and improved sensitivity in weak-signal regimes.
Findings
Achieves sensitivity comparable to the $ ext{F}$-statistic in day-long searches.
Outperforms existing semi-coherent search statistics for short segments.
Demonstrates state-of-the-art sensitivity across diverse segment lengths.
Abstract
We generalize the targeted -statistic for continuous gravitational waves by modeling the -prior as a half-Gaussian distribution with scale parameter . This approach retains analytic tractability for two of the four amplitude marginalization integrals and recovers the standard -statistic in the strong-signal limit (). By Taylor-expanding the weak-signal regime (), the new prior enables fully analytic amplitude marginalization, resulting in a simple, explicit statistic that is as computationally efficient as the maximum-likelihood -statistic, but significantly more robust. Numerical tests show that for day-long coherent searches, the weak-signal Bayes factor achieves sensitivities comparable to the -statistic, though marginally lower than the standard -statistic (and the Bero-Whelan…
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Taxonomy
TopicsGeophysics and Gravity Measurements · Statistical and numerical algorithms
