The lecture will be given by Professor Michielsen.
Computational physics encompasses a huge variety of topics. Therefore, the lecture can only cover a limited fraction of computational physics problems.
- What is computational physics and what is it used for? Traditional versus non-traditional computational physics
- Random numbers and their applications (random number generators, random walk, cellular automata, lattice Boltzman method, event-by-event simulations)
- Monte Carlo method (integration, statistical error, radioactive decay, percolation, importance sampling, Ising model, Markov chains, Metropolis Monte Carlo method)
- Molecular dynamics method (Runge Kutta, predictor-corrector, Euler, Euler-Cromer, Verlet, leap-frog, velocity Verlet, Hamiltonian splitting, accuracy and stability ,force calculations: truncation and shift of potentials, linked list method)
- Diffusion equation (random walk, Brownian motion, Crank-Nicolson, product formula approach, Chebychev algorithm, matrix exponential, stability and accuracy)
- Computational electrodynamics (Maxwell equation, FDTD: Yee algorithm and product formula approach, ADI, multipole methods, finite element method, dissipative materials, UPML)
- Time-(in)dependent Schrödinger equation (Leap-frog, Crank-Nicolson, product formula, Lanczos, Davidson, linear algebra: Gauss, LU decomposition)
- Exact diagonalization
- Quantum Monte Carlo method
- Lectures: The students will obtain an overview of various numerical methods to solve by computer a variety of problems in science.
- Exercises: The students will write their own computer programs for problems drawn from various areas of physics, selected such that they can be worked out in a reasonable time frame, with reasonable computational resources (PC is sufficient).
- T. Pang, An introduction to computational physics, Cambridge Univ. Press.
- J. M. Thijssen, Computational physics, Cambridge Univ. Press
D. P. Landau, K. Binder, A Guide to Monte-Carlo Simulations in Statistical
Physics, Cambridge Univ. Press.
W. H. Press, S. A. Teukolsky, W. T. Wetterling, and B. P. Flannery,
Numerical Recipes: the Art of Scientific Computing, Cambridge Univ. Press.
For more details, you can also refer to the university calender:
Mon. 8.30am - 10am
4282 (28 B 110)
24.04.2017 (12 dates)
|Mon. 10.15am - 11.45am||4282 (28 B 110)||24.04.2017 (12 dates)|
Wed. 8.15am - 9.45am
|CIP Pool 28A 203||26.04.2017 (13 dates)|