Studies

201
Compulsory

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This course presents methods to compute thermodynamic( equilibrium) and kinetic properties from simulation data. Methods to generate such data are discussed, complementing "Methods of Molecular Simulaion" course.

Topics: brief repition of statistical mechanics: ensembles, phase space, equilibrium distribution; Metropolis and Markov chain Monte-Carlo; Molecular Dynamics; Hybrid Monte-Carlo; Transition matrix; Correlation Funcions

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

 

Cross-language

201 157
Compulsory

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AncillaryCourses

Computational Molecular Physics

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Nursing Mother

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