Tensor network representations and beyond
Followed the tensor network course of last semester, this course would continue to introduce more advanced representations of tensor networks.
The main content includes the symmetric tensor network representation, the tensor network representation of topological states of quantum matter, concepts of probability modeling, quantum simulation and quantum error correction as well as their connections with tensor networks.
The main content includes the symmetric tensor network representation, the tensor network representation of topological states of quantum matter, concepts of probability modeling, quantum simulation and quantum error correction as well as their connections with tensor networks.
Lecturer
Date
15th March ~ 7th June, 2022
Website
Prerequisite
basic knowledge of tensor networks
Video Public
No
Notes Public
No
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.