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:

1. Basics of machine learning (for physicists)
2. Finding phase transitions/data analysis
   1. Physics background
   2. Regression and regularization
   3. Dimensional reduction and clustering
   4. Neural networks
3. neural network quantum states
   1. tomography
   2. finding ground states / vmc
4. 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.