Tensornetzwerke

What it is about

You will learn the mathematical foundations and the graphical notation of tensor networks and their application to the approximation of high-dimensional data. In the end you will be able to assess tensor network methods and apply them to problems such as simulation of strongly correlated quantum systems or probabilistic sampling.

What you will be able to do

• Familiarity with formal tensor network formalism
• Proficient handling of graphical notation of tensor networks
• Assessment and application of tensor network approximations for high-dimensional data
• Knowledge of algorithms for simulating strongly correlated quantum systems
• Understanding of backpropagation through tensor network operations and sampling procedures

What the module consists of

• VorlesungConveying the mathematical formalism and the graphical representation
• ÜbungDeepening the lecture content and creatively applying the knowledge

Teaching method

• Tafelvortrag / TabletExplanation of the mathematical formalism and the graphical representation
• ÜbungenFostering understanding and practical application of the methods learned in the lecture