Computational Physics

Lecturer: Carsten Urbach

 

Date: We. 10 Uhr c.t. weekly

 

Place: Seminar Room II, HISKP

 

Tutorials take place in the CIP pool at AVZ:

  • dates to be fixed

 

Credit Points: 7

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 physics problems

The lecture takes place every Wednesday at 10 am c.t. in SR 2, HISKP. Language will be English.

 

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 among others:

  • Ising model
  • XY model
  • Percolation
  • traveling salesman problem
  • fractal growth
  • Random walks und polymer-chains
  • cellular automata
  • path integral monte carlo

 

Literature:

  • W.H. Press et al.: Numerical Recipes in C (Cambridge University Press)
    http://library.lanl.gov/numerical/index.html
  • 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++: www.cprogramming.com/tutorial.html