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Detectability of strongly lensed gravitational waves using model-independent image parameters

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arxiv 2210.01873 v1 pith:FBY4KCLR submitted 2022-10-04 gr-qc astro-ph.HEhep-th

classification gr-qcastro-ph.HEhep-th
keywords parametersgravitationalimagelenslensedlensingsignaldelta
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abstract

Strong gravitational lensing of gravitational waves (GWs) occurs when the GWs from a compact binary system travel near a massive object. The mismatch between a lensed signal and unlensed templates determines whether lensing can be identified in a particular GW event. For axisymmetric lens models, the lensed signal is traditionally calculated in terms of model-dependent lens parameters such as the lens mass $M_L$ and source position $y$. We propose that it is useful to parameterize this signal instead in terms of model-independent image parameters: the flux ratio $I$ and time delay $\Delta t_d$ between images. The functional dependence of the lensed signal on these image parameters is far simpler, facilitating data analysis for events with modest signal-to-noise ratios. In the geometrical-optics approximation, constraints on $I$ and $\Delta t_d$ can be inverted to constrain $M_L$ and $y$ for any lens model including the point mass (PM) and singular isothermal sphere (SIS) that we consider. We use our model-independent image parameters to determine the detectability of gravitational lensing in GW signals and find that for GW events with signal-to-noise ratios $\rho$ and total mass $M$, lensing should in principle be identifiable for flux ratios $I \gtrsim 2\rho^{-2}$ and time delays $\Delta t_d \gtrsim M^{-1}$.

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Cited by 3 Pith papers

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

  1. The diffraction-lensing interpretation of GW231123 with astrophysical priors

    astro-ph.CO 2026-07 conditional novelty 6.0 of 10

    GW231123 is better fit by a lower-mass merger diffracted by an isolated ~1000 M_sun lens, but astrophysical priors and a frequentist rate estimate make this lensing interpretation unlikely.

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

    gr-qc 2026-07 conditional novelty 6.0 of 10

    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.

  3. Parameter estimation of microlensed gravitational waves with Conditional Variational Autoencoders

    gr-qc 2024-11 conditional novelty 5.0 of 10

    A conditional variational autoencoder trained on simulated microlensed binary black hole signals estimates lens mass and source offset with well-calibrated posteriors, runs about 10,000 times faster than Bilby, and cu...

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