TESLA-X: An effective method to search for sub-threshold lensed gravitational waves with a targeted population model
Alvin K. Y. Li, Juno C. L. Chan, Heather Fong, Aidan H. Y. Chong, Alan J. Weinstein, Jose M. Ezquiaga
Published: 2023/11/10
Abstract
Strong gravitational lensing can produce copies of gravitational-wave signals from the same source with the same waveform morphologies but different amplitudes and arrival times. Some of these strongly-lensed gravitational-wave signals can be demagnified and become subthreshold. We present TESLA-X, an enhanced approach to the original GstLAL-based TargetEd Subthreshold Lensing seArch (TESLA) method, for improving the detection efficiency of these potential subthreshold lensed signals. TESLA-X utilizes lensed injections to generate a targeted population model and a targeted template bank. We compare the performance of a full template bank search, TESLA, and TESLA-X methods via a simulation campaign, and demonstrate the performance of TESLA-X in recovering lensed injections, particularly targeting a mock event. Our results show that the TESLA-X method achieves a maximum of $\sim 10\%$ higher search sensitivity compared to the TESLA method within the subthreshold regime, presenting a step towards detecting the first lensed gravitational wave. TESLA-X will be employed for the LIGO-Virgo-KAGRA's collaboration-wide analysis to search for lensing signatures in the fourth observing run.