Brief Introduction to Tensor Network algorithms

Introduction

This course will focus on the basic concepts and representative algorithms of tensor networks. For 1D tensor networks, we will introduce the Matrix Product State(MPS) and its Density Matrix Renormalization Group algorithm(DMRG), Time Evolution Block Decimation algorithm(TEBD), etc. For high-dimensional tensor networks, we will include the Projected Entangled Pair States (PEPS) and its various Tensor Renormalization Group algorithms, as well as the Corner Transfer Matrix Renormalization Group algorithm, variational algorithms, etc. We will also involve some machine learning algorithms and quantum simulation algorithms based on tensor networks if time permits.

Audience

Graduate

Lecturer Intro

Song Cheng is an Assistant Research Fellow at the Yanqi Lake Beijing Institute of Mathematical Sciences and Applications (BIMSA). He holds a PhD in theoretical physics from the Institute of Physics, CAS, and previously served as an Assistant Professor at the Center of Quantum Computing in Pengcheng Laboratory. His current research focuses on investigating the relationship between machine learning, quantum many-body physics, and quantum computing through tensor networks.