Speaker
Description
When a gravitational wave signal encounters a massive object, such as a galaxy or galaxy cluster, it undergoes strong gravitational lensing, producing multiple copies of the original signal. These strongly lensed signals exhibit identical waveform morphology in the frequency domain, allowing analysis without the need for complex lens models. However, stellar fields and dark matter substructures within the galactic lens introduce microlensing effects that alter the morphologies of individual signals. Identifying these microlensing signatures is computationally challenging within Bayesian frameworks. In this study, we propose a residual test to efficiently search for microlensing signatures by leveraging the fact that current Bayesian inference pipelines are optimized solely for the strong lensing hypothesis. Using cross-correlation techniques, we investigate the microlensing-induced deviations from the strong lensing hypothesis, which are imprinted in the residuals. Most simulated signals from our realistic microlensing populations exhibit small mismatches (MMs) between the microlensed and unlensed waveforms, but a fraction show significant deviations. We find that 28% (52%) and 34% (66%) of microlensed events with MM ≥0.03 and ≥0.1, respectively, can be discerned with O4 (O5) detector sensitivities, which demonstrates that high-MM events are more likely to be identified as microlensed. Including all events from a realistic population, 11% (21.5%) are identifiable with O4 (O5) sensitivity using our approach.
