上海交通大学

报告摘要：

The study of strongly correlated fermionic systems, crucial for understanding condensed matter physics, has been significantly advanced by numerical computational methods. Among these, the Determinant Quantum Monte Carlo (DQMC) method stands out for its ability to provide exact numerical solutions. However, the computational complexity of DQMC, particularly in dealing with large system sizes and the notorious sign problem, limits its applicability. We introduce an innovative approach to enhance DQMC efficiency through the implementation of submatrix updates. Building upon the foundational work of conventional fast updates and delay updates, our method leverages a generalized submatrix update algorithm to address challenges in simulating strongly correlated fermionic systems with both onsite and extended interactions at both finite and zero temperatures. We demonstrate the method's superiority by comparing it with previous update methods in terms of computational complexity and efficiency. Specifically, our submatrix update method significantly reduces the computational overhead, enabling the simulation of system sizes up to 8,000 sites without pushing hard. This advancement allows for a more accurate determination of the finite temperature phase diagram of the 3D Hubbard model at half-filling. Our findings not only shed light on the phase transitions within these complex systems but also pave the way for more effective simulations of strongly correlated electrons, potentially guiding experimental efforts in cold atom simulations of the 3D Hubbard model.

报告人简介：

Xiao Yan Xu (许霄琰) graduated with a Ph.D. from the Institute of Physics, Chinese Academy of Sciences in 2017. He has conducted postdoctoral research at the Hong Kong University of Science and Technology and the University of California, San Diego. In 2021, he joined the School of Physics and Astronomy at Shanghai Jiao Tong University. His main research interests include the theory and computation of strongly correlated electron systems, including quantum spin liquids, non-Fermi liquids, the sign problem, quantum criticality, quantum entanglement, and the interdisciplinary intersections of quantum many-body physics with machine learning, quantum information, and ultracold atomic physics.

邀 请 人：吴泉生 特聘研究员

联 系 人：王慧颖 why@iphy.ac.cn

腾讯会议：285-901-036

会议密码：2024

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