Teaching by Annabelle Bohrdt
Teaching
Winter term 2023/24: Numerical methods for quantum many-body systems
Contents:
1. Intro to quantum many-body systems
2. Exact Diagonalization
3. Monte Carlo Methods
4. Matrix Product States
5. Neural quantum states
How:
Each topic will consist of a introduction to the technique, practical exercises (coding) and presentations of research results from the current literature using these techniques.
When & Where:
Tuesdays 11am-1pm and Thursdays 12pm-2pm in 5.0.21 and on zoom (email me for the zoom link).
Summer term 2023: Machine learning for quantum many body physics
Contents:
Basics of machine learning (for physicists)
Finding phase transitions/data analysis
Physics background
Regression and regularization
Dimensional reduction and clustering
Neural networks
neural network quantum states
tomography
finding ground states / vmc
optimization & control
Each topic consists of a introduction of the techniques, hands-on implementations, and examples of applications in current research on quantum many-body systems.
We meet in 5.0.21 and on zoom (email me for link) on Tuesdays at 11:00 and Thursdays at 11:30.