Theory of Tensor Network representations
Having completed the tensor network course from the previous semester, this course will delve deeper into advanced tensor network representations. It will cover a range of topics, including symmetric tensor network representations, tensor network representations of the topological states of quantum matter, concepts of probability modeling, quantum simulation, and quantum error correction. Furthermore, the course will explore the connections between these topics and tensor network representations
Lecturer
Date
11th March ~ 27th May, 2024
Location
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| Monday | 13:30 - 16:55 | A3-2a-302 | ZOOM 05 | 293 812 9202 | BIMSA |
Prerequisite
basic knowledge of quantum mechanics is required
Syllabus
week 1：general introduction
week 2-3: theory of matrix product states
week 4: symmetric tensor networks
week 5-6: tensor network representation of SPT state
week 7-8: 2D TN representations and lattice gauge model
week 9: special topics in quantum error correction
week 10: fusion category in TN representations
week 11: fermionic TN representation
week 12: special topics in quantum circuit & quantum monte carlo
week 2-3: theory of matrix product states
week 4: symmetric tensor networks
week 5-6: tensor network representation of SPT state
week 7-8: 2D TN representations and lattice gauge model
week 9: special topics in quantum error correction
week 10: fusion category in TN representations
week 11: fermionic TN representation
week 12: special topics in quantum circuit & quantum monte carlo
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).
Audience
Advanced Undergraduate
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.