Analytic weak-signal approximation of the Bayes factor for continuous gravitational waves
arXiv:2409.13069 · doi:10.1088/1361-6382/adb097
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 approximation). In semi-coherent searches over short (compared to a day) segments, this approximation matches or outperforms the weighted dominant-response -statistic and returns to the sensitivity of the (weighted) -statistic for longer segments. Overall the new Bayes-factor approximation demonstrates state-of-the-art or improved sensitivity across a wide range of segment lengths we tested (from 900s to 10days).
27 pages, 4 figures, submitted to CQG v2: added appendix showing translation to 5-vector framework v3: fixed minor equation typos (incl sign error in Appendix A), corrigendum submitted to CQG
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