Anthony Chen [UC Berkeley]

Abstract: Since the 1980s, simulation of many-body quantum systems has been viewed as one of the killer applications of quantum computers. Yet computing thermal equilibrium properties—central to materials science, chemistry, and statistical physics—remains a major algorithmic challenge. In this talk, I will present a foundational algorithmic framework for preparing quantum thermal states. The framework can be understood both as a quantum analog of Markov chain Monte Carlo (MCMC) and as a succinct model of system–bath interactions. Together, these perspectives suggest a concrete route toward useful early applications of quantum computers.  Research interests: Chi-Fang Chen (Anthony) works at the intersection of quantum computation, statistical physics, and high-dimensional probability. He received his PhD in Physics in quantum information science from Caltech in 2024. His research develops new quantum algorithmic principles toward practical quantum advantage, where deep theoretical ideas can have a practical impact. Please sign up here to meet with the speaker.