Computational Physics

LecturerCarsten Urbach


Date: Tu. 10 Uhr c.t. weekly


Place: Seminar Room I, HISKP


Credit Points: 7


eCampus: the course is connected to an eLearning module on eCampus. Please become member of this module on eCampus.

This lecture intends to introduce to modern Monte-Carlo methods used in physics. The content is, among others:

  • Statistical Models, Likelihood, Bayesian and Bootstrap Methods
  • Random Variable Generation
  • Stochastic Processes
  • Monte-Carlo Methods
  • Markov-Chain Monte-Carlo
  • application of these methods to lattice field theory and statistical models
  • parallel programming using, e.g. MPI, openMP or CUDA

The lecture is implemented as an eLearning course. The lecture material will be provided online. Tutorials will be held every Tuesday at 10 am c.t. in SR 1, HISKP. Language will be English. Participation in the tutorials is a requirement for passing the module.


For passing this module students are requested to independently complete a small project where they apply the knowledge presented in this lecture to model problems from field theory and statistical physics. Projects will be published soon. We also require participation in the tutorials for passing this module!



  • W.H. Press et al.: Numerical Recipes in C (Cambridge University Press)
  • C.P. Robert and G. Casella: Monte Carlo Statistical Methods (Springer 2004)
  • Tao Pang: An Introduction to Computational Physics (Cambridge University Press)
  • Vesely, Franz J.: Computational Physics: An Introduction (Springer)
  • Binder, Kurt and Heermann, Dieter W.: Monte Carlo Simulation in Statistical Physics (Springer)
  • Fehske, H.; Schneider, R.; Weisse, A.: Computational Many-Particle Physics (Springer)
  • Learning C and C++:
  • DeGrand, T. and DeTar C.: Lattice methods for quantum chromodynamics (World Scientific)
  • Rothe, H. J.: Lattice Gauge Theories: An Introduction (World Scientific)
  • Münster, G and Montvay, I.: Quantum fields on a lattice (Cambridge University Press)