Computational Physics

 

Lecture details

The lecture will be given by Professor Mazzarello.

Description:

Computational physics encompasses a huge variety of topics. Therefore, the lecture can only cover a limited fraction of computational physics problems.
Topics include:

  • 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

Learning goals:

  • 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).

Literature:

  • 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:

Time Room Start/Finish

Mon. 10.15am - 11.45am

4282 (28 B 110)

09.04.2018 - 16.07.2018 (14 dates)

Wed. 8.15am - 9.45am TBA 11.04.2018 - 18.07.2018 (14 dates)

Wed. 1.15pm - 2.45pm

4282 (28 B 110) 11.04.2018 - 18.07.2018 (12 dates)