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Exploring the Impact of Microlensing on Gravitational Wave Signals: Biases, Population Characteristics, and Prospects for Detection

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arxiv 2306.11479 v2 pith:IEFI56M2 submitted 2023-06-20 astro-ph.CO gr-qc

Anuj Mishra , Ashish Kumar Meena , Anupreeta More , Sukanta Bose This is my paper · ORCID
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keywords microlensingpopulationsignalsdetectionimpactmathrmmicrolensedparameters
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abstract

In this study, we investigate the impact of microlensing on gravitational wave (GW) signals in the LIGO$-$Virgo sensitivity band. Microlensing caused by an isolated point lens, with (redshifted) mass ranging from $M_\mathrm{Lz}\in(1,10^5){\rm M}_\odot$ and impact parameter $y\in (0.01,~5)$, can result in a maximum mismatch of $\sim 30\%$ with their unlensed counterparts. When $y<1$, it strongly anti-correlates with the luminosity distance enhancing the detection horizon and signal-to-noise ratio (SNR). Biases in inferred source parameters are assessed, with in-plane spin components being the most affected intrinsic parameters. The luminosity distance is often underestimated, while sky-localisation and trigger times are mostly well-recovered. Study of a population of microlensed signals due to an isolated point lens primarily reveals: (i) using unlensed templates during the search causes fractional loss ($20\%$ to $30\%$) of potentially identifiable microlensed signals; (ii) the observed distribution of $y$ challenges the notion of its high improbability at low values ($y\lesssim 1$), especially for $y\lesssim 0.1$; (iii) Bayes factor analysis of the population indicates that certain region in $M_\mathrm{Lz}-y$ parameter space have a higher probability of being detected and accurately identified as microlensed. Notably, the microlens parameters for the most compelling candidate identified in previous microlensing searches, GW200208_130117, fall within a 1-sigma range of the aforementioned higher probability region. Identifying microlensing signatures from $M_\mathrm{Lz}<100~$M$_\odot$ remains challenging due to small microlensing effects at typical SNR values. Additionally, we also examined how microlensing from a population of microlenses influences the detection of strong lensing signatures in pairs of GW events, particularly in the posterior-overlap analysis.

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Cited by 7 Pith papers

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

  1. Detectability of lensed gravitational waves in matched-filtering searches

    gr-qc 2024-11 conditional novelty 7.0 of 10

    Matched-filtering searches recover strongly lensed gravitational waves at rates far below optimal-SNR predictions, with detection efficiency dropping to under one percent.

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    The rate of compound gravitational-wave lensing by intermediate-mass black holes in globular clusters is at most about 10^-3 of galaxy-scale lensed events, disfavoring GW231123 as such an event.

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    Eccentric BBH signals can masquerade as wave-optics microlensing in quasicircular analyses, but eccentric recovery templates break the degeneracy.

  4. Biases in Tests of General Relativity from Microlensed Gravitational-Wave Signals

    gr-qc 2026-07 conditional novelty 5.0 of 10

    Microlensing in the wave-optics regime can push standard LIGO-Virgo-KAGRA general-relativity tests to false ~4–4.5σ deviations, even for signals that are perfectly consistent with GR.

  5. Discovering gravitational waveform distortions from lensing: A deep dive into GW231123

    gr-qc 2025-12 conditional novelty 5.0 of 10

    GW231123's apparent gravitational-lensing signal has a false-alarm probability around 4σ, so the event cannot be claimed as lensed under the two-image wave-optics model.

  6. 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.

  7. 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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