Research Areas

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COSMOLOGY

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Cosmology is the study of the nature of the universe as a whole entity. The word cosmology is derived from the Greek kosmos meaning harmony or order. Cosmologists study the formation, evolution, and future of the universe and its constituents. There exist many models to study the universe in cosmology, and the most well-established among them as per the current understanding is the concordance model. Numerous efforts are going on among the researchers to constraint the value of cosmological parameters of the well-established standard cosmological ΛCDM model. Observations from the various ground and sky-based missions and surveys tend to rule out the non-standard models and increase and evaluate the current understanding of the concordance model. Saurabh S. and Shwetank S. (mentors/co-lead of XCAR) and trainees together research in various sub-fields of cosmology.

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GRAVITATIONAL-WAVE PHYSICS

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• Neutron Star waveform Modelling led by Bhashin Thakore

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• Gravitational Wave lensing led by Shashwat Singh

Just as light tends to deviates due to the presence of the massive body in its path (null geodesic) gravitational waves also show a similar phenomenon which is called gravitational wave lensing. In this phenomenon, multiple images of the same source are observed with different amplification and different time delays. Gravitational waves lensing opens a new method to probe the universe.

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SHADOWS OF BLACK HOLE

Recent observations from the EHT (Event Horizon Telescope) of the centre of the M87 galaxy have opened a new era for testing general relativity using black hole images. Normally, the astrophysical black holes are thought to be described by the Kerr metric from General relativity. Still, theories beyond general relativity predict black holes that deviate from the Kerr solution. To test the Kerr hypothesis and hence GR, we are developing a framework that can perform theory-independent tests of general relativity by analyzing black hole images. The process includes modelling the black hole neighbourhood, building and comparing black hole images, and using Bayesian analysis on the EHT data to estimate the deviation parameters that characterize deviations from the Kerr solution. However, this work is also extended to other compact objects such as Naked singularities and Wormholes, which mimic a Blackhole's behaviour. Still, it presents good alternatives to conventional modelling and analysis.
Using this framework, we are also trying to search for Dark matter candidates by modelling different profiles and constraining with recent observations of S2* Orbit and EHT.

The projects are mentored by Saurabh K. 

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NEURAL NETWORKS (Deep learning and Machine learning) using ASTRONOMICAL DATA

Deep learning and Machine Learning has been extensively used in redefining search methods in astronomy and has been extremely effective in various fields. Shashwat Singh and Adarsh Mahor have been actively working in the field.