Tensor renormalization group method and its applications

The tensor renormalization group is a new class of numerical methods developed 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.