During the last two decades, tensor networks have emerged as a powerful new language for encoding the wave functions of quantum many-body states, and the operators acting on them, in terms of contractions of tensors. Insights from quantum information theory have led to highly efficient and accurate tensor network representations for a variety of situations, particularly for one- and two-dimensional (1d, 2d) systems. For these, tensor network-based approaches rank among the most accurate and reliable numerical methods currently available.
This course offers an introduction to these numerical methods.

Einführung in die Astrophysik. Schwerpunkt: Sterne und Planeten.

Bitte hier im LSF anmelden. Der Zugangsschlüssel zum Moodle-Kurs wird den Teilnehmern mitgeteilt.

This tutorial and exercise accompanies the lecture Medical Physics Aspects in Ion Beam Therapy in Clinical Practice. A registration for this tutorial is strongly recommended for all participants of the lecture.

In the tutorial we will recap some aspects of the lecture and answer questions, we will solve together in-class exercises, preparing you for working at home on the short weekly exercise sheet. The exercise sheets should be handed-in and will be corrected.

Please register on LSF.

The confrontation of theories with data is at the core of modern sciences. In astrophysics state of the art statistical methods are used to assess and improve models. In this course you will learn from first principles the basics of Bayesian statistics. The course aims that you gain an intuition of which methods to apply in different situations. An important concept is the role of priors. It is only in comparison to prior knowledge that data can inform you about a model. In particular we will study the following topics:

  1. Foundations of Bayesian Statistics
  2. Parameter Estimation - Simple Cases
  3. Parameter Estimation - Advanced Topics
  4. Model Selection
  5. Probabilities
  6. Non-parametric estimation
  7. Design of Experiments
  8. Extensions of Least-Square Methods
  9. Monte Carlo Markov Chain Sampling

The core of the course is not just the lecture. You will learn with hands on problem sheets to tackle statistical problems with the help of experienced tutors.

Please self enroll into the course and register on LSF here.
(Upon registration in LSF you will be send an enrollment key for Moodle)