36th Annual Report (2023-24)

24 microlensing effects are ignored, it can cause bias in the inference of various parameters of binary black holes, for example, their distances, masses, spins and so on. We have identified which part of the microlensing parameters space is easier to be detected in the observations. A GW event called GW200208_130117 seems to arise from this detectable part of the microlensing parameter space. However, due to the low SNR of the GW event, one cannot be confident of its nature and needs to do further investigation. [MNRAS, In press (2024)] Microlensing by population of stars and stellar remnants embedded in stronglensinggalaxy: Anuj Mishra, Anupreeta More, Sukanta Bose and collaborators developed a framework to determine microlensing by population of stellar/stellar remnant population embedded in strong lenses. The strong lensing magnification was found to be the most important parameter that affected the severity of microlensing distortions in the lensed GW signals [MNRAS, 508, 4869 (2021)]. Essentially, all lensed GW signals with strong lensing magnification <10 showed no deviation from unlensed signals [MNRAS, 517, 872 (2022)]. In subsequent studies, we also showed that if strong lensing + microlensing effects are not accounted for during the strong lensing searches in GW data, then this can adversely affect detection of lensed GW signals [MNRAS, In press (2024)]. Improving the ranking statistics of strongly lensed signals: Anupreeta More and Surhud More proposed using joint distributions of strongly lensed image properties such as the time delays and relative magnifications to better select pairs of strongly lensed gravitational wave events in the data. The improvement was demonstrated by generating a mock sample of lensed and unlensed gravitational events. Furthermore, the new ranking statistics called Mgal was also applied to the known GW events which improved their ¬ ¬ significances, in particular for GW190731-GW190803 which seemed to be more consistent with a lensed population [MNRAS, 515, 1044 (2023)]. The importance of using joint distributions, which relies on a specific lens mass model, was further tested by Anupreeta More and collaborators to show that there was more benefit in using Mgal when searching for strongly lensed pair of candidate events [MNRAS 519, 2046 (2024)]. Rapid detection of strongly lensed GW signals with machine learning: Sourabh Magare, Anupreeta More and collaborators have developed the SLICK pipeline which uses a neural network to analyse a pair of GW events and decide whether these are likely to be strongly lensed. In this work, the signals are cross-correlated with Sine-Gaussian functions and the resulting projection maps for the pair of events seen in two LIGO detectors are analysed simultaneously. For a lensed pair of events, we expect similar projections compared to a random pair of unlensed events. We find that our network is able to show good performance on a mock sample of lensed and unlensed events as well as the real known GW events from the third observing run of LIGO- Virgo data [arXiv:2403.02994]. Early-Warning with Gravitational- Lensing: Sourabh Magare, Shasvath J. Kapadia and Anupreeta More have developed a method to alert electromagnetic telescopes of the merger of a binary neutron star, well before it merges, provided the BNS is gravitationally lensed. This method will enable telescopes to capture electromagnetic emissions before the merger, resulting in highly exciting and potentially ground-breaking observations. [Astrophys. J. Lett., 955, L31 (2023)] Constraints on compact dark matter fromgravitationalwavemicrolensing: If a significant fraction of dark matter is in the form of compact objects, they will cause microlensing effects in the GW ¬ ¬ ¬ signals observable by the ground-based detectors. ApratimGanguly, Shasvath J. Kapadia and their collaborators have developed a method to constrain the fraction of compact dark matter to be less than ≃ 50-80 % in the mass range 2 5 10 -10 M from the (non-)observation ☉ of microlensing signatures in the LIGO- Virgo observing runs. These modest constraints will be significantly improved in the next few years with the expected detection of thousands of binary black hole events, providing a new avenue to probe the nature of dark matter. [Astrophys. J. Lett. 926 L28 (2022)] Detection and parameter estimation challenges of type-II lensed signals: Type-II lensed GW signals introduce additional distortions in the strains of the BBH signals depending on various morphologies. Apratim Ganguly and his collaborators investigated the potential applicability of these distortions in helping identify Type-II signals from a single detection. They also investigated the systematic biases that could arise in the inference of their parameters if they are unknowingly recovered with gravitational-wave templates that do not take the distortion into account. It can be shown that the lensing distortions will allow to confidently identify Type-II images for highly inclined binaries: at network signal-to- noise ratio (SNR) ρ = 20 (50), individual Type-II images should be identifiable with log Bayes factor ln ℬ > 2 for inclinations ɩ > 5 π/ 12 ( π/ 3). [Phys. Rev. D108, 043036 (2023)] Expansion rate of the Universe: The Hubble constant measures the local expansion rate of the Universe. As part of the LVK Collaboration, IUCAA researchers used 47 gravitational wave sources fromthe Third LVK Gravitational Wave Transient Catalog (GWTC-3) to estimate the Hubble constant H_0. Each GW signal provides the luminosity distance to the source, and researchers ¬ ¬ Cosmology