Non-Equilibrium Computer Simulation Algorithms

Phil Attard

in Non-equilibrium Thermodynamics and Statistical Mechanics

Published in print October 2012 | ISBN: 9780199662760
Published online January 2013 | e-ISBN: 9780191745287 | DOI:
Non-Equilibrium Computer Simulation Algorithms

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Three non-equilibrium computer simulation algorithms are presented in detail: stochastic molecular dynamics, non-equilibrium Monte Carlo, and Brownian dynamics. Stochastic molecular dynamics is based on the stochastic dissipative equations of motion, which do not suffer the disadvantages of non-Hamiltonian deterministic equations or thermostats. Extensive numerical tests are performed for steady heat flow and for a driven Brownian particle in a solvent. A non-equilibrium Monte Carlo algorithm is based upon the non-equilibrium probability distribution. Umbrella sampling and other methods to improve the efficiency of the algorithm are discussed. Results are compared with the stochastic molecular dynamics and with Nose-Hoover equilibrium molecular dynamics. Brownian dynamics using the simple Langevin equation is outlined. The perturbation theory of the preceding chapter is used for a more advanced algorithm suited for concentrated dispersions and macromolecules. The stochastic calculus is discussed in the context of Brownian dynamics and the generalised Langevin equation

Keywords: non-equilibrium; simulation; molecular dynamics; Monte Carlo; Brownian dynamics; stochastic calculus

Chapter.  30361 words.  Illustrated.

Subjects: Condensed Matter Physics

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