Speaker: Yang Zhang, University of Tennessee, Knoxville

Title: Electron Pairing and Fractionalization in the Age of AI and Quantum Computing

Abstract:

Electrons in solids can do two remarkable things: they can pair up and flow without resistance, and they can collectively behave as fractionally charged particle. Predicting either remains a major challenge because the physics spans enormous spatial scales and exponentially large quantum state spaces. In this talk, I will show how my group uses artificial intelligence to tackle these challenges. Machine-learned Hamiltonians reproduce moiré electronic structures with meV accuracy for systems of up to millions of atoms, enabling studies of superconductivity from weak to strong coupling in twisted semiconductors. For the second, we turn to quantum processors. which can directly represent and manipulate highly entangled states. Constant-depth circuits prepare 18 fractional quantum Hall states up to 156 qubits. Remarkably, some of the most exotic states are also the easiest to prepare. Together, these efforts show how AI can extend quantum-materials modeling to realistic scales, while quantum processors open access to states beyond classical reach.

Bio: Yang Zhang is an Assistant Professor of Physics at the University of Tennessee, Knoxville. He earned his bachelor’s degree in physics and mathematics from Tsinghua University in 2015, followed by a Ph.D. in Physics from the Max Planck Dresden in 2019, then he worked as a postdoc at MIT until 2022. Dr. Zhang has received several awards, including two overall Winner Awards in the World Supercomputing Contest, SFB Best Doctoral Thesis Award, the Tschirnhaus Medal from the Leibniz Association, the Otto-Hahn Medal of the Max Planck Society, International Union of Pure and Applied Physics (IUPAP) Early Career Scientist Prize in Computational Physics, and Haslam family professor from UT Knoxville.  Dr. Zhang's research focuses on topological and correlated quantum states, quantum transport, and quantum computation, using a combined first-principle and many-body simulation approach. 

Refreshments at 3:45pm in Lewis 104