Dr. Sugata Chowdhury awarded a DOE grant

Assistant Professor of Physics, Dr. Sugata Chowdhury, was recently awarded the Department of Energy grant ($2.7 million for three years). This project proposal aims to study quantum magnetism and exotic quantum states of low-dimensional materials. Prof. Chowdhury will serve as the grant PI and work closely with his Co-PIs from Northeastern University, the SLAC, and Standford University.

The interplay between magnetism and topology has led to many applicable phenomena, such as large anomalous Hall effect, extremely large negative magnetoresistance, topological Hall effect, and anomalous thermoelectric response. A new direction in this field is to control topology in momentum space by controlling magnetism in direct space. This is possible in topological semimetals with different magnetic ground states that are nearly degenerate. Here we propose a neutron study of such material, namely EuAgAs, NiPS3, etc. The research team’s focus is machine learning quantum magnetism. By taking advantage of innovative capabilities at the DOE’s Linac Coherent Light Source II to provide novel experimental data of these low-energy modes of the system that are not accessible anywhere else with x-rays, together with an extensive theoretical framework including three of the most powerful, modern computational approaches (exact diagonalization, advanced density functional theory, and the density matrix renormalization group), we have an opportunity to make fundamental advancements in the understanding of materials. The coupling of the scientific domain of quantum materials (experiment with theory and computation) with rapid advances in high-performance computing and multimodal experimental workflows is a key advancement that gives this project an unmatched potential to make important breakthroughs in real-time, machine-assisted quantum magnetism. Not only will the hand-picked team of multi-institute experts lay the groundwork for this unique opportunity, but we have targeted three specific areas where data science will not only accelerate scientific discovery but enable solutions for fundamental basic energy sciences challenges that would otherwise not be possible.