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

TL;DR

This paper introduces a rapid and accurate Bayesian method for identifying and analyzing strongly lensed gravitational-wave events, significantly improving computational efficiency for future large-scale gravitational-wave data analysis.

Contribution

The paper presents a novel Bayesian approach that leverages prior-posteriors substitution and lookup tables to efficiently analyze multiple strongly lensed gravitational-wave images.

Findings

Method enables analysis of large candidate sets with reduced computational cost.

Applicable to any number of lensed images, including quadruplets.

Demonstrated effectiveness with simulated data.

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.