Turning Selection Bias into a New Statistic: Asymmetry and Fringes of Lensed Gravitational Waves
Year: 2026
Type: preprint
Abstract: Gravitational waves (GWs) propagating across the Universe can be distorted by intervening lenses, producing characteristic wave-optics signatures. These effects are not incorporated into current matched-filtering searches and can therefore substantially reduce detection efficiency. The underlying mechanism is the signal-consistency test, which measures deviations between the observed and expected signal-to-noise ratio (SNR) distributions. We report a systematic study of the impact of gravitational lensing on signal-consistency tests, using a two-image interference model and representative signal-consistency statistics in both the time and frequency domains. We find that overlapping images produce sharply localized SNR residuals in the time domain, breaking the reflection symmetry of the autocorrelation about the merger time. Although interference fringes produce broadband SNR residuals in the frequency domain, both domains exhibit a minimum for high-mass signals when the fringe structure becomes comparable to the signal bandwidth. This highlights a limitation of current strategies that search for distorted lensed signals only among GW events detected by matched-filtering searches. Exploiting this asymmetry, we develop a statistic that separates selected down-ranked lensed injections from noise-background triggers and paired nonlensed injections, without extending the template bank. Our results establish the first connection between lensing observables and detection, paving the way for the discovery of lensed GWs.
Source: arXiv (Cornell University)
Authors: Chan, Juno C. L., Li, Elwin K. Y.
Institutions: University of Copenhagen, Chinese University of Hong Kong
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
Funders: National Science Foundation, National Research Foundation, Ministry of Education, Culture, Sports, Science and Technology, Academia Sinica, Centre National de la Recherche Scientifique, Chinese University of Hong Kong, Istituto Nazionale di Fisica Nucleare, Ministry of Science and ICT, South Korea, National Science and Technology Council, Science and Technology Facilities Council, Japan Society for the Promotion of Science
Awards: G7203848545, G7969654205
OpenAlex ID: W7221771660