基于张量网络的机器学习与量子计算算法
张量网络最早是一种用来处理量子多体系统数值计算的代数结构。由于其表示系统局域关联具有独特的优势，近几年来开始被越来越多地应用于机器学习与量子计算领域。这门课的前半段我会先讲解处理量子多体波函数的传统张量网络算法，之后将重心集中在介绍张量网络在上述两个新领域的一系列发展。同时，考虑到此方向涵盖的预备知识跨度较大。我也会在课程中根据听众反馈有侧重地补充部分机器学习和量子计算的相关预备知识。
Lecturer
Date
2nd March ~ 13th May, 2021
Location
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| Monday,Wednesday | 13:30 - 15:05 | - | - | - |
Prerequisite
量子力学
Reference
• Orus, R. Annals of Physics 349, 117–158 (2014).
• Orus, R. The European Physical Journal B 87, (2014).
• Schollwoeck, U. Annals of Physics 326, 96–192 (2011).
• Verstraete, F., Cirac, J. I. & Murg, V. Advances in Physics 57, 143–224 (2008).
• Orus, R. The European Physical Journal B 87, (2014).
• Schollwoeck, U. Annals of Physics 326, 96–192 (2011).
• Verstraete, F., Cirac, J. I. & Murg, V. Advances in Physics 57, 143–224 (2008).
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.