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)


    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. 


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