Abstract:
Nearly four decades have passed since the discovery of the first cuprate high-Tc superconductor, yet the mechanism remains elusive. A crucial task in understanding the mechanism is identifying its effective microscopic model. The two-dimensional Hubbard model is widely regarded as the model for cuprates. Although the Hubbard model is remarkably simple in form, the accurate solution of it in two-dimension is very difficult. Consequently, despite being proposed over 60 years ago, its properties remain a subject of debate. Over the past few decades, researchers have developed numerous many-body methods to tackle strongly correlated quantum many-body problems. However, because different methods often employ distinct approximations, the solutions to the Hubbard model frequently yield conflicting results.
In the past decade, thanks to advancements in strongly correlated quantum many-body methods and cross-validation among different approaches, researchers have gradually begun to form a degree of consensus regarding the ground state of the two-dimensional Hubbard model. Recent studies on the ground state suggest that the Hubbard model with next-nearest-neighbor hopping may be the "correct" model for describing cuprate high-Tc superconductivity.
Biography:
Qin Mingpu obtain his bachelor's degree from Beihang University in 2008 and his Ph.D. from the Institute of Physics, Chinese Academy of Sciences in 2013. He then conducted postdoctoral research at the College of William & Mary. From 2014 to 2018, he was also a member of the Simons foundation collaboration on the many-electron problem. In January 2019, he joined the School of Physics and Astronomy at Shanghai Jiao Tong University as a tenure-track associate professor. His research focuses on the strongly correlated quantum many-body systems in condensed matter physics. His main interest lies in the development of accurate and efficient many-body methods for studying strongly correlated many-body systems, including density matrix renormalization group (DMRG), tensor network states related methods, and the auxiliary-field quantum Monte Carlo (AFQMC). He has made contributions to addressing the fermion sign problem and improving density matrix renormalization group techniques. With collaborators, his long-term research on the Hubbard model has led to significant progress in understanding its ground state properties.
Seminar by the NYU-ECNU Institute of Physics at NYU Shanghai