Gold Medalist, M.Sc. Physics - Central University of Rajasthan

B.Sc. Physics, Honours - University of Calcutta

1) Aditya-L1 Project (Aditya-L1 Support Cell)

https://al1ssc.aries.res.in/present_members

As a part of the Adtiya-L1 Support Cell, we will be developing software to utilise the processed data from the payloads on board the Aditya-L1.

2) Multiwavelength study of the physical processes happening in the middle corona of the Sun: The Sun is our nearest star, and therefore, it is very well observed. The solar atmosphere comprises layers with different plasma beta (the ratio between gas pressure and magnetic pressure). The variation of the plasma beta from greater than one in the solar photosphere to less than one in the solar corona determines the relative importance of the plasma pressure and magnetic pressure in governing the dynamics of the solar atmosphere. Similarly, magnetic field topology changes from closed to open (locally) magnetic fields while moving through the middle corona, which is defined as a region of solar atmosphere encompassing 1.5-6 solar radii. This region is not well explored due to the lack of multiwavelength observations.

In this project, we aim to study the dynamics and structure of the middle corona. We will study the origin and dynamics of transients in the middle corona using the data from the newly launched Solar Ultraviolet Imager/GOES-R, Solar Orbiter, SDO, K-Cor, and Aditya-L1. Furthermore, we will create an automated catalogue that will offer the opportunity to study the long-term variation of the middle corona of the Sun.

3) Using computational model to simulate CMEs and understand their impact on Planetary atmosphere: We will be using Block Adaptive Tree Solarwind Roe Upwind Scheme (BATSRUS) (Powell et al., 1999; Gombosi et al., 2001), an open-source magnetohydrodynamic (MHD) code. The BATSRUS code solves 3D MHD equations in finite volume form using numerical methods related to Roe's Approximate Riemann Solver. BATSRUS uses an adaptive grid composed of rectangular blocks arranged in varying degrees of spatial refinement levels (CCMC Metadata Registry (CMR)). This code uses parallel computing via Message Passing Interface (MPI) to perform these sophisticated calculations. We will inject flux rope into the model and simulate flux rope CMEs using global coronal models such as Gibson and Low, GL (Gibson, S.E. and Low, B.C., 1998). Later on, we will use data-driven models to understand the origin and evolution of these solar eruptions, enabling us in Space Weather.

4) Developing deep learning models for automated detection CMEs: Space weather predictions work hand in hand with observational evidence. The Variable Emission Line Coronagraph (VELC) payload on board is a state-of-the-art coronagraph that will be observing the solar Corona from 1.05 to 3 Solar radii with very high spatial and time resolution, ideal for studying CME origin and propagation through the inner and middle corona. For this project, being a member of the Aditya-L1 Support Cell (a joint collaboration between ARIES and ISRO), we will develop in-house deep learning and AI/ML models (Asensio Ramos, A., Cheung, M.C.M., Chifu, I. et al, 2023) for automated detection of coronal mass ejections whenever they pass through the field of view of Aditya-L1’s VELC payload. This will not only expedite space weather predictions but also alert us in case an Earth-directed CME is detected.

1. Das, P., & Bose, R., 2024, ISRO’s recent Space Odyssey, India Calling, Vol. XV (3-10), Center for Bharat Studies, Research Institute for Languages and Cultures of Asia, Mahidol University.