ICTS

I am an Integrated PhD student at ICTS–TIFR, working with Dr. Pallavi Bhat. My research interests lie in theoretical and computational astrophysics, particularly magnetohydrodynamics (MHD), turbulence and the origin of astrophysical magnetic fields. I combine analytical models with numerical simulations to understand how magnetic fields grow and evolve, especially during the formation of astrophysical systems through gravitational collapse. More broadly, I am interested in mathematical physics and cosmology, and in the connections between mathematical descriptions and physical phenomena.

My doctoral research focuses on the growth and nonlinear saturation of turbulent dynamos—the conversion of turbulent kinetic energy into magnetic energy. Dynamo action provides a leading explanation for the amplification and maintenance of magnetic fields in astrophysical systems. One direction of my research explores dynamos in collapsing turbulent plasmas, extending dynamo theory to evolving environments relevant to star and galaxy formation. Another investigates what determines the strength and structure of magnetic fields at saturation, when their feedback on the flow becomes significant. Using statistical closure models alongside numerical simulations, I explore highly turbulent regimes that are difficult to access through direct numerical simulations alone.

My research papers include:

1. Turbulent dynamos in a collapsing cloud
   Muhammed Irshad P, Pallavi Bhat, Kandaswamy Subramanian and Anvar Shukurov.
   Preprint, arXiv:2503.19131
   Physical Review Letters 136, 091201 (2026).

   General-audience coverage: APS Physics, ICTS and Ashoka University.

2. Small-scale dynamo saturation across magnetic Prandtl numbers using the EDQNM closure
   Muhammed Irshad, Kandaswamy Subramanian and Pallavi Bhat.
   Preprint, arXiv:2607.02743 (2026).

3. Collapse-accelerated small-scale dynamos in the first stars and galaxies
   Muhammed Irshad and Pallavi Bhat.
   Preprint, arXiv:2610.02389 (2026).

My computational work uses Athena++ and Dedalus for numerical simulations, together with Python for data analysis and visualization.