Introduction to Tensor Network Algorithms
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.
Lecturer
Date
13th September ~ 6th December, 2022
Website
Prerequisite
Quantum Mechanics
Reference
1. Orus, R. Annals of Physics 349, 117–158 (2014).
2. Orus, R. The European Physical Journal B 87, (2014).
3. Schollwoeck, U. Annals of Physics 326, 96–192 (2011).
4. Verstraete, F., Cirac, J. I. & Murg, V. Advances in Physics 57, 143–224 (2008).
2. Orus, R. The European Physical Journal B 87, (2014).
3. Schollwoeck, U. Annals of Physics 326, 96–192 (2011).
4. Verstraete, F., Cirac, J. I. & Murg, V. Advances in Physics 57, 143–224 (2008).
Audience
Graduate
Video Public
No
Notes Public
No
Language
Chinese
Lecturer Intro
Song Cheng is an Assistant Professor 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.