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    Using overlap of sky localization probability maps for filtering potentially lensed pairs of gravitational-wave signals

    Henry W. Y. Wong1,2,*,†, Lok W. L. Chan1,*,‡, Isaac C. F. Wong3,4,1,§, Rico K. L. Lo5,6,∥, and Tjonnie G. F. Li1,3,4,7,¶

    • 1Department of Physics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong
    • 2Department of Statistics and Data Science, University of Texas at Austin, Austin, Texas 78712, USA
    • 3KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Kasteelpark Arenberg 10, 3001 Leuven, Belgium
    • 4Leuven Gravity Institute, KU Leuven, Celestijnenlaan 200D box 2415, 3001 Leuven, Belgium
    • 5Center of Gravity, Niels Bohr Institute, Blegdamsvej 17, 2100 Copenhagen, Denmark
    • 6LIGO Laboratory, California Institute of Technology, Pasadena, California, California 91125, USA
    • 7Institute for Theoretical Physics, KU Leuven, Celestijnenlaan 200D, B-3001 Leuven, Belgium

    • *These authors contributed equally to this work: Henry W. Y. Wong, Lok W. L. Chan.
    • †Contact author: wyhwong@link.cuhk.edu.hk
    • ‡Contact author: lokwlc@link.cuhk.edu.hk
    • §Contact author: chunfung.wong@kuleuven.be
    • ∥Contact author: kalok.lo@nbi.ku.dk
    • Contact author: tjonnie.li@kuleuven.be

    Phys. Rev. D 112, 124005 – Published 1 December, 2025

    DOI: https://doi.org/10.1103/qc7y-z9hy

    Abstract

    Strong gravitational lensing creates multiple images of a gravitational wave transient. The current state-of-the-art method for identifying such lensing events is a computationally expensive full Bayesian analysis. In this paper, we investigate the feasibility and efficiency of using the overlap of sky localization probability maps (skymaps) to quickly filter potentially lensed gravitational wave signal pairs. We introduce three overlap statistics and test their performance using 200 simulated lensed pairs of gravitational-wave signals across five sets of signal-to-noise ratios. By setting a threshold with a false positive rate of FPR=10−2 for the three overlap statistics, we find that we can filter out over 99% of nonlensed events while retaining all lensed events. The statistics for each event pair can be computed instantly, and can be used in practice to quickly analyze existing events using the skymaps from the low-latency localization pipelines when results from the full parameter estimation are not available.

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