(in Polish) Computer simulations in physics

This course is not intended for students who completed Symulacje komputerowe w fizyce (1100-3`SKwF). We use Python for assignments in the computer lab, however some initial help with the Python syntax will be provided. Experience in programming is not strictly necessary, but it may be of significant help in completing computer projects.

Classroom

The purpose of this course is to introduce students to computer simulations and their applications to physical problems. It is a combination of review-like lectures and computer labs. Topics include Molecular Dynamics, Monte Carlo methods, network models and simple quantum systems. Classes are centered on presenting various modeling techniques and improving programming skills.

1. Introduction: what is the benefit of using computer simulation models?

2. Crash course on Python.

3. Molecular Dynamics:

- Newtonian mechanics

- numerical integration

- simulation of noble gases

4. Probabilistic models:

- percolation

- Monte Carlo methods

- Ising model

5. Network models:

- diffusion-limited aggregation

- self-organized criticality

- Wa-Tor

D. Frenkel and B. Smit, Understanding Molecular Simulation: From Algorithms to Applications, Academic Press (1996).

M.P. Allen, D.J. Tildesley, Computer Simulation of Liquids, Oxford (1989).

M.E.J. Newman and G.T. Barkema, Monte Carlo methods in statistical physics, Oxford (1999).

J.M. Thijssen, Computational Physics, Cambridge (1999).

The students are asked to prepare a short presentation summarizing one topic from the lectures. The final grade consists of computer based projects in the lab (80%) and two short tests (20%).