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Residual test to search for microlensing signatures in strongly lensed gravitational wave signals

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arxiv 2503.02186 v2 pith:YZR43RDJ submitted 2025-03-04 gr-qc astro-ph.IM

classification gr-qcastro-ph.IM
keywords microlensingeventsgravitationalmicrolensedsignalsignalssignaturesstrong
verification ladder T0 review T1 audit T2 compute T3 formal
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When a gravitational wave signal encounters a massive object, such as a galaxy or galaxy cluster, it undergoes strong gravitational lensing, producing multiple copies of the original signal. These strongly lensed signals exhibit identical waveform morphology in the frequency domain, allowing analysis without the need for complex lens models. However, stellar fields and dark matter substructures within the galactic lens introduce microlensing effects that alter individual signal morphologies. Identifying these microlensing signatures is computationally challenging within Bayesian frameworks. In this study, we propose a residual test to efficiently search for microlensing signatures by leveraging the fact that current Bayesian inference pipelines are optimized solely for the strong lensing hypothesis. Using cross-correlation techniques, we investigate the microlensing-induced deviations from the strong hypothesis, which are imprinted in the residuals. Most simulated signals from our realistic microlensing populations exhibit small mismatches between the microlensed and unlensed waveforms, but a fraction show significant deviations. We find that 28% (52%) and 34% (66%)of microlensed events with mismatch > 0.03 and > 0.1, respectively, can be discerned with O4 (O5) detector sensitivities, which demonstrates that high-mismatch events are more likely to be identified as microlensed. Including all events from a realistic population, 11% (21.5%) are identifiable with O4 (O5) sensitivity using our approach.

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Forward citations

Cited by 3 Pith papers

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  1. Across the Universe: GW231123 as a magnified and diffracted black hole merger

    astro-ph.GA 2025-12 conditional novelty 6.0 of 10

    GW231123's extreme mass and spins may be explained by a point-mass microlens embedded in a galaxy, reducing the inferred source mass to about 100-180 solar masses.

  2. Accelerated inference of microlensed gravitational waves with machine learning

    astro-ph.CO 2025-11 conditional novelty 5.0 of 10

    A neural posterior estimator trained on wave-optics-microlensed gravitational-wave signals recovers source and lens parameters and Bayes factors consistent with Bilby, about 10 times faster.

  3. When vacuum breaks: a self-consistency test for astrophysical environments in extreme mass ratio inspirals

    gr-qc 2025-10 conditional novelty 5.0 of 10

    A duration-scan self-consistency test on vacuum EMRI parameter posteriors flags unmodeled environmental effects without adding environmental parameters.

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