This course offers an introduction to computer simulation methods for physics problems and their implementation on PCs and super computers. The covered topics include classical equations of motion, partial differential equations (wave equation, diffusion equation, Maxwell's equations), Monte Carlo simulations, percolation, phase transitions, and N-Body problems.

This course offers an introduction to computer simulation methods for physics problems and their implementation on PCs and super computers. The covered topics include classical equations of motion, partial differential equations (wave equation, diffusion equation, Maxwell's equations), Monte Carlo simulations, percolation, phase transitions, and N-Body problems.

Computer simulation methods in statistical physics. Classical Monte-Carlo-simulations: finite-size scaling, cluster algorithms, histogram-methods, renormalization group. Application to Boltzmann machines. Simulation of non-equilibrium systems.Molecular dynamics simulations: long range interactions, Ewald summation, discrete elements, parallelization.

This is the first of two courses, introducing particle accelerators from a theoretical point of view and covers state-of-the-art modelling techniques.

Non-linearities in beam dynamics of charged particles will be discussed. Lie-Methods in combination with differential algebra (DA) and truncated power series (TPS) will be used. We will use statistical mechanics to study storage rings and free electron lasers. Crystalline beams and quantum mechanics effects will be analysed towards possible a use of accelerator in quantum sensing.

In this seminar the students present a paper on advanced topics in theoretical and/or computational physics. This includes the reproduction and derivation of presented results or implementation of algorithms.