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Bayesian framework to follow-up continuous gravitational wave candidates from deep surveys

J. Martins1,2,*, M. A. Papa1,2, B. Steltner1,2, R. Prix1,2, and P. B. Covas1,2,3

  • *Contact author: jasper.martins@aei.mpg.de
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Phys. Rev. D 113, 023041 – Published 22 January, 2026

DOI: https://doi.org/10.1103/rbyp-157m

Abstract

Broad all-sky searches for continuous gravitational waves have high computational costs and require hierarchical pipelines. The sensitivity of these approaches is set by the initial search and by the number of candidates from that stage that can be followed up. The current follow-up schemes for the deepest surveys require careful tuning and setup, and have a significant human-labor cost and this impacts the number of follow-ups that can be afforded. Here we present and demonstrate a new follow-up framework based on Bayesian parameter estimation for the rapid, highly automated follow-up of candidates produced by the early stages of deep, wide-parameter space searches for continuous waves.

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Phys. Rev. D 113, 023041– Published 22 January, 2026
  • Received 7 September 2025
  • Accepted 10 December 2025
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Open access publication funded by the Max Planck Society.

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