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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

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

classification gr-qc astro-ph.HEhep-th
keywords parametersgravitationalimagelenslensedlensingsignaldelta
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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 4 Pith papers

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

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    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

    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. Identification of Lensed Gravitational-Wave Beat Patterns by LISA

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    Strong lensing of MBHBs produces identifiable beat patterns in about 7% of detectable two-image LISA events, with Bayesian inference recovering time delay and magnification parameters.

  4. Parameter inference of millilensed gravitational waves using neural spline flows

    gr-qc 2025-05 conditional novelty 6.0

    Neural spline flows perform fast posterior inference on 11-dimensional millilensed GW parameters with accuracy comparable to dynesty for most quantities and a 3-day to 0.8-second speedup.