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

TL;DR

This paper studies how microlensing affects gravitational wave signals in LIGO-Virgo data, revealing biases in parameter estimation, detection challenges, and potential for identifying microlensed events, especially in specific parameter regions.

Contribution

It provides the first detailed analysis of microlensing impacts on GW signals, including biases, detection prospects, and population-level implications, using Bayesian methods and population modeling.

Findings

Microlensing can cause up to 30% mismatch in GW signals.

Detection of microlensed signals is reduced by 20-30% when using unlensed templates.

Certain microlens parameters have higher detection probabilities, with some candidates matching predicted regions.

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.