Understanding Molecular Simulation: From Algorithms to
Applications
D. Frenkel, and B. Smit. Computational Science Series Academic Press, San Diego, Second edition, (2002)
Abstract
An advanced text on the physics and computation of
atomistic simulations. Chapter titles are:
introduction; statistical mechanics; Monte Carlo
simulations; molecular dynamics simulations; Monte
Carlo simulations in various ensembles; molecular
dynamics in various ensembles; free energy
calculations; the Gibbs ensemble; other methods to
study coexistence; free energies of solids; free
energy of chain molecules; long-range interactions;
biased Monte Carlo schemes; accelerating Monte Carlo
sampling; tackling time-scale problems; rare events;
dissipative particle dynamics. Appendices are
entitled: (the) Lagrangian and Hamiltonian;
non-Hamiltonian dynamics; linear response theory;
statistical errors; integration schemes; saving CPU
time; reference states; statistical mechanics of the
Gibbs ``ensemble''; overlapping distribution for
polymers; some general purpose algorithms; small
research projects; hints for programming.
%0 Book
%1 dfrenkel96:mc
%A Frenkel, Daan
%A Smit, Berend
%B Computational Science Series
%C San Diego
%D 2002
%I Academic Press
%K Carlo Monte dynamics fortran mechanics molecular physics programming statistical
%T Understanding Molecular Simulation: From Algorithms to
Applications
%V 1
%X An advanced text on the physics and computation of
atomistic simulations. Chapter titles are:
introduction; statistical mechanics; Monte Carlo
simulations; molecular dynamics simulations; Monte
Carlo simulations in various ensembles; molecular
dynamics in various ensembles; free energy
calculations; the Gibbs ensemble; other methods to
study coexistence; free energies of solids; free
energy of chain molecules; long-range interactions;
biased Monte Carlo schemes; accelerating Monte Carlo
sampling; tackling time-scale problems; rare events;
dissipative particle dynamics. Appendices are
entitled: (the) Lagrangian and Hamiltonian;
non-Hamiltonian dynamics; linear response theory;
statistical errors; integration schemes; saving CPU
time; reference states; statistical mechanics of the
Gibbs ``ensemble''; overlapping distribution for
polymers; some general purpose algorithms; small
research projects; hints for programming.
%Z Series editors: D. Frenkel, M. Klein, M. Parrinello and B. Smit. First edition published in 1996.
%7 Second
@book{dfrenkel96:mc,
abstract = {An advanced text on the physics and computation of
atomistic simulations. Chapter titles are:
introduction; statistical mechanics; Monte Carlo
simulations; molecular dynamics simulations; Monte
Carlo simulations in various ensembles; molecular
dynamics in various ensembles; free energy
calculations; the Gibbs ensemble; other methods to
study coexistence; free energies of solids; free
energy of chain molecules; long-range interactions;
biased Monte Carlo schemes; accelerating Monte Carlo
sampling; tackling time-scale problems; rare events;
dissipative particle dynamics. Appendices are
entitled: (the) Lagrangian and Hamiltonian;
non-Hamiltonian dynamics; linear response theory;
statistical errors; integration schemes; saving CPU
time; reference states; statistical mechanics of the
Gibbs ``ensemble''; overlapping distribution for
polymers; some general purpose algorithms; small
research projects; hints for programming.},
added-at = {2013-03-21T02:24:53.000+0100},
address = {San Diego},
annote = {Series editors: D. Frenkel, M. Klein, M. Parrinello and B. Smit. First edition published in 1996.},
author = {Frenkel, Daan and Smit, Berend},
biburl = {https://www.bibsonomy.org/bibtex/27058bda2c1d06e4718bf4fe7a9e5b1d0/drmatusek},
edition = {Second},
interhash = {3e1272dc52ef1545e92ab3973adf0f18},
intrahash = {7058bda2c1d06e4718bf4fe7a9e5b1d0},
keywords = {Carlo Monte dynamics fortran mechanics molecular physics programming statistical},
publisher = {Academic Press},
series = {Computational Science Series},
timestamp = {2013-03-21T02:24:54.000+0100},
title = {Understanding Molecular Simulation: From Algorithms to
Applications},
volume = 1,
year = 2002
}