报告题目：Tensor network renormalization

报 告 人：杨硕，加拿大Perimeter理论物理研究所

报告时间：2016年3月30日15：00

报告地点：理科楼三楼报告厅（C302）

报告摘要：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.