Magnetic Orders, Stripes, and Superconductivity - Insights from Computations on the Hubbard Model
The Hubbard model is fundamental to quantum many-body physics. Since the discovery of high-temperature superconductivity, it has been a focal point in condensed matter and more recently also in the field of ultracold atoms. The properties of the two-dimensional Hubbard model are often the outcome of a delicate balancing act between multiple competing or co-existing tendencies. This makes it extremely demanding for computational approaches to determine the properties - and make predictions (e.g., as a function of parameter values) which can serve as a guide to theory and experiments. Recently, significant progress has been made via advances in algorithms and the combined use of complementary methods in a multi-messenger manner. The speaker will discuss some of these developments, what they have revealed about the physics of the Hubbard model, and the prospect of accurate and systematic computations in more realistic quantum systems.
About the Speaker
Prof. ZHANG Shiwei received his BS from the University of Science and Technology of China and his PhD from Cornell University. He held the position of Chancellor Professor of Physics at the College of William & Mary until 2021. He is currently the Senior Research Scientist/Group Leader at the Center for Computational Quantum Physics of the Flatiron Institute in New York.
Prof. Zhang is an international leader in the study of quantum systems by Monte Carlo approaches. Methods he pioneered have been applied in condensed matter, quantum chemistry, ultra-cold atoms, and nuclear physics. He is a Fellow of the American Physical Society and has received a number of awards for his research and teaching including the NSF CAREER Award, the Cottrell Scholar Award, and the William and Mary Plumeri Award for Faculty Excellence.
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