张量重正化群方法及其应用

Tensor renormalization group method and its applications

张量重正化群方法是近年来发展起来的一种新的数值计算方法,它将经典配分函数和量子波函数的张量网络表示与重正化群方法相结合,在强关联系统的数值研究中,发挥着越来越重要的作用。文章以经典统计模型和量子格点模型为例,简要介绍了张量重正化群的一些基础知识和研究给定物理模型的一般性思路,并对张量重正化群未来可能的发展方向和亟待解决的问题进行了讨论。

The tensor renormalization group is a new class of numerical methods devel- oped in recent years. It combines the tensor network representations of the classical partition function and quantum wave function with the renormalization group techniques, and plays a more and more important role in the numerical study of strongly correlated systems. Taking the classical statistical models and quantum lattice models as two examples, we give a brief introduction to its basics and the general routine for studying a given physical model, and discuss possible future developments as well as the problems that need to be solved in this field.