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General

Lecture: Petra Imhof, Frank Noé, Marcus Weber, Burkhard Schmidt
Exercise: tba
Language: English
SWS: 2+2, LP/ECTS: 5
Students: MSc Physics, MSc Mathematics

Dates

Lecture Mondays 12-14 Arnimallee 14 0.1.01 (Hörsaal B) starting 14 April
Exercise Tuesdays 16-18 Arnimallee 14 1.4.03 (Seminarraum T2) starting 22 April

Content

This module teaches the theoretical basics and simulation techniques for simple stochastic systems (e.g. molecular models, ising models, diffusion in model potentials). Physical principles for stochastic trajectories and ensembles are combined with simulation techniques that are able to generate appropriate data. In more detail, we will cover:
  • Statistical mechanics: basis and derivations to the most important physical ensembles. Boltzmann distribution, Partition function, Expectations
  • Monte-Carlo simulation: Theory, construction, convergence and implementation of Monte Carlo methods for the computation of stationary expectation values
  • Kinetics: Rate theories, time correlations and other time-dependent expectations
  • Molecular dynamics simulation: Theory, construction, convergence and implementation of MD simulations for the computation of dynamical expectation values

This topic: CompMolBio > Lectures > CompMolPhys
Topic revision: 10 Apr 2014, KatjaGeiger