简介: |
In recent years, the tensor network approach has become a powerful theoretical and computational tool for studying condensed matter systems. In this talk, I will introduce a tensor renormalization group scheme for coarse-graining a two-dimensional tensor network, which can be successfully applied to both classical and quantum systems on and off criticality. The key idea of this scheme is to deform a 2D tensor network into small loops and then optimize tensors on each loop. In this way we remove short-range entanglement at each iteration step, and significantly improve the accuracy and stability of the renormalization flow. I will demonstrate our algorithm in the classical Ising model and a frustrated 2D quantum model.
个人简介：杨硕，加拿大Perimeter理论物理研究所博士后。主要从事量子物理与凝聚态理论的相关研究,目前集中在张量网络算法在量子多体系统中的应用。
工作经历：2014.9-今 加拿大Perimeter理论物理研究所博士后；2012.9-2014.8 德国马普量子光学所博士后；2010.7-2012.8 美国马里兰大学博士后
教育经历：2006.9-2010.6 中国科学院理论物理研究所理学博士；2002.9-2006.6 南开大学理学学士 |
