Abstract Details
| Name: Aniruddha Chakraborty Affiliation: Tata Institute of Fundamental Research, Mumbai Conference ID: ASI2025_385 Title : GLANCE: Gravitational Lensing Authenticator using Non-modelled Cross-correlation Exploration in Search for Lensed GW Signals Authors and Co-Authors : Aniruddha Chakraborty 1, Suvodip Mukherjee 1 Abstract Type : Oral Abstract Category : Galaxies and Cosmology Abstract : Gravitational lensing occurs when massive astrophysical objects distort spacetime, causing electromagnetic (EM) waves or gravitational waves (GWs) to deflect from their paths. Depending on the wavelength of the GW in relation to the size of the lensing object, two regimes arise: microlensing and strong lensing. When the GW wavelength is comparable to or larger than the lens, microlensing occurs, leading to frequency-dependent modulations. Conversely, strong lensing arises when the wavelength is much smaller than the lens, yielding frequency-independent effects. By the third observation run, the LIGO-Virgo-KAGRA detector network had detected over 90 GW events, yet no confident lensing events. To address this, we developed GLANCE (Gravitational Lensing Authenticator using Non-modelled Cross-correlation Exploration) to search for lensed GW signals. This is a first-in-class approach to detect lensed GWs through finding the similarities of lensed GW signals at the strain level overlap. GLANCE utilizes distinct cross-correlation methods tailored to each lensing regime. For strong lensing, GLANCE cross-correlates between noisy reconstructions of lensed signals, enhancing the similarity between signals while suppressing noise. A significant deviation from noise cross-correlation indicates a potential lensing candidate. The technique is able to pick up lensed GW signals with a false alarms close to ~0.8/yr, which is very low compared to the pre-existing techniques. For microlensing, GLANCE focuses on residuals obtained by subtracting the best-fit GW from the data. Through testing on simulated data, GLANCE demonstrates a robust false alarm rate at network SNRs around 30. The presence of lensing can bias the inference of the GW source properties. Thus a joint source and lens characterisation was incorporated in GLANCE for their correct inference. Currently, we are applying GLANCE to open GW data, anticipating that with nearly 1000 detections expected from advanced GW detectors and next-generation facilities, at least one lensed GW pair will be identified. |