Introduction to Computational Physics

Lecturer(s)

Prof. H.J. Herrmann

(course operated jointly with Profs. M. Troyer and M. Kröger)

Hour(s) of lecture(s), exercise(s) and credit points

2L
2E
8CP

Teaching goals

This course offers an introduction to computer simulation methods for physics problems and their implementation on PCs and super computers: classical equations of motion, partial differential equations (wave equation, diffusion equation, Maxwell's equation), molecular dynamics, efficient methods for long range forces, Monte Carlo simulations, percolation, phase transitions

Summary and outline

Contents

• Introduction, random numbers (RN)
• RN, Percolation
• Fractals, Cellular Automata
• Finite Size Effects, Monte Carlo
• Importance Sampling, Metropolis
• Ising Model (Troyer)
• Random Walks (Kröger)
• Differential Eqs. (Euler, Runge Kutta..)
• Eqs. of Motion (Newton, Regula Falsi)
• Finite Difference Meth. Relaxation
• Gradient Methods
• Multigrid, Finite Elements Method
• Variational FEM, Crank-Nicholson
• Wave equation, Navier-Stokes

Literature

• H.Gould and J. Tobochnik: Introduction to Computer Simulation Methods (Wesley, 1996)
• D. Landau and K. Binder: A Guide to Monte Carlo Simulations in Statistical Physics (Cambridge, 2000)
• D. Stauffer, F.W. Hehl, V. Winkelmann and J.G. Zabolitzky: Computer Simulation and Computer Algebra (Springer, 1988)
• K. Binder and D.W. Heermann: Monte Carlo Simulation in Statistical Physics (Springer; 1997)
• N.J. Giordano: Computational Physics (Pearson, 1996)
• J.M. Thijssen: Computational Physics (Cambridge, 1999)

Computational Physics @ ETH

The introduction is continued by the following three complementary lectures:

• Computational Quantum Physics 402-0810-00L (2L, 2E, 8 CP)
  by Prof. M. Troyer/Dr. P. De Forcrand.(D-PHYS).
• Computational Statistical Physics 402-0812-00L (2L, 2E, 8 CP)
  by Prof. H.J. Herrmann (D-BAUG)
• Computational Polymer Physics 327-5102-00L (2L, 2E, 4 CP)
  by Prof. M. Kröger (D-MATL)