Monte Carlo Simulation of Condensed Matter Systems
Dr. Gerhard Besold
Membrane and Statistical Physics Group (MEMPHYS)
Department of Chemistry, DTU
- November 12:
``From Roulette to Integrals''
The basic philosophy of Monte Carlo simulation
Random number generation. Monte Carlo integration. Importance sampling.
Markov processes. Stationary distribution and detailed balance condition.
- November 19:
``Flipping Spins and Hopping Particles''
The modeling of many particle systems in statistical physics
Spin and lattice gas models. Applications in surface science. Modeling of
soft condensed matter. Basics of statistical physics reviewed. Phase transitions
and phase diagrams. Universality.
- November 26:
``Gambling with Boltzmann factors''
Monte Carlo simulation of many particle systems
Monte Carlo simulation in various statistical ensembles. General strategy and details of
implementation. Equilibration and data reduction. Finite-size scaling.
- December 3:
``Dealing with Histograms''
Advanced Monte Carlo simulation techniques
Distribution functions and spectral free energies. Histogram reweighting
techniques. Localization of phase boundaries. Strategies to overcome free
energy barriers (shape function method, entropic and multi-canonical sampling).
Gibbs ensemble simulations.
- December 10::
Dr. Michael Promberger
(Institute for Theoretical Physics I, Univ. of Erlangen-Nürnberg, Germany)
``Phase transitions in finite systems and the micro-canonical ensemble''
- December 17:
``What Happened after the Quench''
Monte Carlo simulation of non-equilibrium phenomena
Phase separation processes and domain growth. Universality in growth kinetics. Lifshitz-Slyozhov
and Lifshitz-Allen-Cahn growth laws. Case studies.