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A fast and precise methodology to search for and analyse strongly lensed gravitational-wave events

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arxiv 2105.04536 v2 pith:UIZVPUWQ submitted 2021-05-10 gr-qc astro-ph.HE

A fast and precise methodology to search for and analyse strongly lensed gravitational-wave events

classification gr-qc astro-ph.HE
keywords gravitational-wavelensedimagesmethodologypairsstronglyanalyseevents
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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abstract

Gravitational waves, like light, can be gravitationally lensed by massive astrophysical objects such as galaxies and galaxy clusters. Strong gravitational-wave lensing, forecasted at a reasonable rate in ground-based gravitational-wave detectors such as Advanced LIGO, Advanced Virgo, and KAGRA, produces multiple images separated in time by minutes to months. These images appear as repeated events in the detectors: gravitational-wave pairs, triplets, or quadruplets with identical frequency evolution originating from the same sky location. To search for these images, we need to, in principle, analyze all viable combinations of individual events present in the gravitational-wave catalogs. An increasingly pressing problem is that the number of candidate pairs that we need to analyse grows rapidly with the increasing number of single-event detections. At design sensitivity, one may have as many as $\mathcal O(10^5)$ event pairs to consider. To meet the ever-increasing computational requirements, we develop a fast and precise Bayesian methodology to analyse strongly lensed event pairs, enabling future searches. The methodology works by replacing the prior used in the analysis of one strongly lensed gravitational-wave image by the posterior of another image; the computation is then further sped up by a pre-computed lookup table. We demonstrate how the methodology can be applied to any number of lensed images, enabling fast studies of strongly lensed quadruplets.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Identifying lensed gravitational waves with physics-informed posterior learning

    gr-qc 2026-07 conditional novelty 6.0

    Fusing a simulation-trained common-source mass posterior with waveform features raises lensed-event detection efficiency from 20.8% to 35.2% at 1% false-positive rate and lowers the SNR for 50% efficiency from 45.3 to 33.5.

  2. GW231123: False Massive Graviton Signatures from Unmodeled Point-Mass Lensing

    gr-qc 2026-04 unverdicted novelty 6.0

    Unmodeled point-mass lensing produces a spurious nonzero graviton mass posterior in GW231123 that vanishes when lensing is included in the analysis.

  3. Machine Learning Assisted Parameter-Space Searches for Lensed Gravitational Waves

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    Normalizing flow based non-Gaussian consistency tests in a compressed detector basis select GW170104-GW170814 as the only promising lensed pair in GWTC-3.

  4. The Science of the Einstein Telescope

    gr-qc 2025-03 unverdicted novelty 3.0

    The paper provides state-of-the-art predictions for the Einstein Telescope's impact on fundamental physics, cosmology, compact-object astrophysics, and multi-messenger astronomy across its proposed configurations.