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.
Learning objective
The lecture will give a deeper insight into computer simulation methods in statistical physics. Thus, it is an ideal continuation of the lecture "Introduction to Computational Physics" of the autumn semester. In the first part students learn to apply the following methods: Classical Monte Carlo-simulations, finite-size scaling, cluster algorithms, histogram-methods, renormalization group. Moreover, students learn about the application of statistical physics methods to Boltzmann machines and how to simulate non-equilibrium systems.
In the second part, students apply molecular dynamics simulation methods. This part includes long range interactions, Ewald summation and discrete elements.
Content
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.
Lecture notes
Lecture notes and slides are available online and will be distributed if desired.
Literature
Literature recommendations and references are included in the lecture notes.
Prerequisites / Notice
Some basic knowledge about statistical physics, classical mechanics and computational methods is recommended.
Performance assessment
Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course