Study on topological phases of matter in strongly correlated systems via deep learning
Abstract
This project is aiming at investigating topological phases of matter in strongly correlated systems via quantum correlations and deep learning. It is crucial to obtain the quantum phase transitions and to identify topological phases due to the exponential growth of the Hilbert space and the lack of local order parameters, respectively. Motivating by those, the project includes alleviating the challenges by applying deep learning techniques with suitable quantum information, which PI has developed in the previous project, either using supervised or unsupervised learning, to characterize the topological phases of matter in strongly correlated systems.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 16, 2024
- Source ID
- FA23862314104
Entities
People
- Ming-chiang Chung
Organizations
- Air Force Office of Scientific Research
- National Chung Hsing University
- United States Air Force