Configurational bias Monte Carlo - Revision history

Carl McBride: /* References */ Added a reference.

2009-09-28T10:39:43Z

References: Added a reference.

← Older revision		Revision as of 12:39, 28 September 2009
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	#[http://dx.doi.org/10.1080/00268979200100061 Jörn Ilja Siepmann and Daan Frenkel "Configurational bias Monte Carlo: a new sampling scheme for flexible chains", Molecular Physics '''75''' pp. 59-70 (1992)]		#[http://dx.doi.org/10.1080/00268979200100061 Jörn Ilja Siepmann and Daan Frenkel "Configurational bias Monte Carlo: a new sampling scheme for flexible chains", Molecular Physics '''75''' pp. 59-70 (1992)]
	#[http://dx.doi.org/10.1088/0953-8984/4/12/006 D. Frenkel, G. C. A. M. Mooij and B. Smit "Novel scheme to study structural and thermal properties of continuously deformable molecules", Journal of Physics: Condensed Matter '''4''' pp. 3053-3076 (1992)]		#[http://dx.doi.org/10.1088/0953-8984/4/12/006 D. Frenkel, G. C. A. M. Mooij and B. Smit "Novel scheme to study structural and thermal properties of continuously deformable molecules", Journal of Physics: Condensed Matter '''4''' pp. 3053-3076 (1992)]
			#[http://dx.doi.org/10.1063/1.462037 Juan J. de Pablo, Manuel Laso, and Ulrich W. Suter "Simulation of polyethylene above and below the melting point", Journal of Chemical Physics '''96''' pp. 2395- (1992)]
	[[category: Monte Carlo]]		[[category: Monte Carlo]]
	[[Category:Computer simulation techniques]]		[[Category:Computer simulation techniques]]

Carl McBride: /* References */ Added another reference.

2008-09-03T13:54:16Z

References: Added another reference.

← Older revision		Revision as of 15:54, 3 September 2008
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	#[http://dx.doi.org/10.1063/1.454200 Jonathan Harris and Stuart A. Rice "A lattice model of a supported monolayer of amphiphile molecules: Monte Carlo simulations", Journal of Chemical Physics '''88''' pp. 1298-1306 (1988)]		#[http://dx.doi.org/10.1063/1.454200 Jonathan Harris and Stuart A. Rice "A lattice model of a supported monolayer of amphiphile molecules: Monte Carlo simulations", Journal of Chemical Physics '''88''' pp. 1298-1306 (1988)]
	#[http://dx.doi.org/10.1080/00268979200100061 Jörn Ilja Siepmann and Daan Frenkel "Configurational bias Monte Carlo: a new sampling scheme for flexible chains", Molecular Physics '''75''' pp. 59-70 (1992)]		#[http://dx.doi.org/10.1080/00268979200100061 Jörn Ilja Siepmann and Daan Frenkel "Configurational bias Monte Carlo: a new sampling scheme for flexible chains", Molecular Physics '''75''' pp. 59-70 (1992)]
	[[category: ~~monte~~ Carlo]]		#[http://dx.doi.org/10.1088/0953-8984/4/12/006 D. Frenkel, G. C. A. M. Mooij and B. Smit "Novel scheme to study structural and thermal properties of continuously deformable molecules", Journal of Physics: Condensed Matter '''4''' pp. 3053-3076 (1992)]
			[[category: Monte Carlo]]
	[[Category:Computer simulation techniques]]		[[Category:Computer simulation techniques]]

Carl McBride: /* References */

2007-06-14T14:44:56Z

References

← Older revision		Revision as of 16:44, 14 June 2007
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	It is usual that many of the accessible configurations have a small probability and only a few ones are probable. In these cases, the simulation is more efficient if the probabilities of the different configurations are previously considered. With this end, the new position for a unit is randomly chosen between a discrete number of possibilities (the neighboring sites in lattice models or a randomly chosen set of positions in other cases), taking into account their [[Boltzmann probabilities]]. In the case of [[polymers]], an entirely new part of a chain up to an end can be generated following a path of easily accessible positions. This introduces a bias which should be compensated by considering a weight factor for each new position chosen (or a product of these factors for a new chain). A similar weight corresponding to reconstructing the old configuration from the new one has also to be calculated. The probability ratios are corrected by introducing the ratio between the new and the old configurational weight factors.		It is usual that many of the accessible configurations have a small probability and only a few ones are probable. In these cases, the simulation is more efficient if the probabilities of the different configurations are previously considered. With this end, the new position for a unit is randomly chosen between a discrete number of possibilities (the neighboring sites in lattice models or a randomly chosen set of positions in other cases), taking into account their [[Boltzmann probabilities]]. In the case of [[polymers]], an entirely new part of a chain up to an end can be generated following a path of easily accessible positions. This introduces a bias which should be compensated by considering a weight factor for each new position chosen (or a product of these factors for a new chain). A similar weight corresponding to reconstructing the old configuration from the new one has also to be calculated. The probability ratios are corrected by introducing the ratio between the new and the old configurational weight factors.
	==References==		==References==
			#[http://dx.doi.org/10.1063/1.454200 Jonathan Harris and Stuart A. Rice "A lattice model of a supported monolayer of amphiphile molecules: Monte Carlo simulations", Journal of Chemical Physics '''88''' pp. 1298-1306 (1988)]
	#[http://dx.doi.org/10.1080/00268979200100061 Jörn Ilja Siepmann and Daan Frenkel "Configurational bias Monte Carlo: a new sampling scheme for flexible chains", Molecular Physics '''75''' pp. 59-70 (1992)]		#[http://dx.doi.org/10.1080/00268979200100061 Jörn Ilja Siepmann and Daan Frenkel "Configurational bias Monte Carlo: a new sampling scheme for flexible chains", Molecular Physics '''75''' pp. 59-70 (1992)]
	[[category: monte Carlo]]		[[category: monte Carlo]]
	[[Category:Computer simulation techniques]]		[[Category:Computer simulation techniques]]

Carl McBride at 13:56, 14 June 2007

2007-06-14T13:56:48Z

← Older revision		Revision as of 15:56, 14 June 2007
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	'''Configurational bias Monte Carlo''' is a [[Monte Carlo]] technique used in the simulation of [[flexible molecules]], ''i.e.''		'''Configurational bias Monte Carlo''' is a [[Monte Carlo]] technique used in the simulation of [[flexible molecules]], ''i.e.''
	molecules that can adopt various configurations.		molecules that can adopt various configurations. For this reason the configurational bias Monte Carlo method has been widely
			applied to simulations of alkanes and [[polymers]].

	It is usual that many of the accessible configurations have a small probability and only a few ones are probable. In these cases, the simulation is more efficient if the probabilities of the different configurations are previously considered. With this end, the new position for a unit is randomly chosen between a discrete number of possibilities (the neighboring sites in lattice models or a randomly chosen set of positions in other cases), taking into account their [[Boltzmann probabilities]]. In the case of [[polymers]], an entirely new part of a chain up to an end can be generated following a path of easily accessible positions. This introduces a bias which should be compensated by considering a weight factor for each new position chosen (or a product of these factors for a new chain). A similar weight corresponding to reconstructing the old configuration from the new one has also to be calculated. The probability ratios are corrected by introducing the ratio between the new and the old configurational weight factors.		It is usual that many of the accessible configurations have a small probability and only a few ones are probable. In these cases, the simulation is more efficient if the probabilities of the different configurations are previously considered. With this end, the new position for a unit is randomly chosen between a discrete number of possibilities (the neighboring sites in lattice models or a randomly chosen set of positions in other cases), taking into account their [[Boltzmann probabilities]]. In the case of [[polymers]], an entirely new part of a chain up to an end can be generated following a path of easily accessible positions. This introduces a bias which should be compensated by considering a weight factor for each new position chosen (or a product of these factors for a new chain). A similar weight corresponding to reconstructing the old configuration from the new one has also to be calculated. The probability ratios are corrected by introducing the ratio between the new and the old configurational weight factors.

Carl McBride at 13:49, 14 June 2007

2007-06-14T13:49:51Z

← Older revision		Revision as of 15:49, 14 June 2007
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	It is ~~usual that many of the accessible configurations have~~ a ~~small probability and only a few ones are probable. In these cases,~~ the simulation ~~is more efficient if the probabilities~~ of ~~the different configurations are previously considered~~. With this end, the new position for a unit is randomly chosen between a discrete number of possibilities (the neighboring sites in lattice models or a randomly chosen set of positions in other cases), taking into account their Boltzmann probabilities. ~~In the case of polymers, an entirely new part of a chain up to an end~~ can ~~be generated following a path of easily accessible positions~~. This introduces a bias which should be compensated by considering a weight factor for each new position chosen (or a product of these factors for a new chain). A similar weight corresponding to reconstructing the old configuration from the new one has also to be calculated. The probability ratios are corrected by introducing the ratio between the new and the old configurational weight factors.		'''Configurational bias Monte Carlo''' is a [[Monte Carlo]] technique used in the simulation of [[flexible molecules]], ''i.e.''
			molecules that can adopt various configurations.

			It is usual that many of the accessible configurations have a small probability and only a few ones are probable. In these cases, the simulation is more efficient if the probabilities of the different configurations are previously considered. With this end, the new position for a unit is randomly chosen between a discrete number of possibilities (the neighboring sites in lattice models or a randomly chosen set of positions in other cases), taking into account their [[Boltzmann probabilities]]. In the case of [[polymers]], an entirely new part of a chain up to an end can be generated following a path of easily accessible positions. This introduces a bias which should be compensated by considering a weight factor for each new position chosen (or a product of these factors for a new chain). A similar weight corresponding to reconstructing the old configuration from the new one has also to be calculated. The probability ratios are corrected by introducing the ratio between the new and the old configurational weight factors.
	==References==		==References==
			#[http://dx.doi.org/10.1080/00268979200100061 Jörn Ilja Siepmann and Daan Frenkel "Configurational bias Monte Carlo: a new sampling scheme for flexible chains", Molecular Physics '''75''' pp. 59-70 (1992)]
	1. I. ~~Siepman~~ and D. Frenkel, ~~Mol. Phys~~. ~~75,~~ 59 (1992).		[[category: monte Carlo]]
			[[Category:Computer simulation techniques]]

Juan at 16:16, 13 June 2007

2007-06-13T16:16:42Z

← Older revision		Revision as of 18:16, 13 June 2007
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	It is usual that many of the accessible configurations have a small probability and only a few ones are probable. In these cases, the simulation is more efficient if the probabilities of the different configurations are previously considered. With this end, the new position for a unit is randomly chosen between a discrete number of possibilities (the neighboring sites in lattice models or a randomly chosen set of positions in other cases), taking into account their Boltzmann probabilities. In the case of polymers, an entirely new part of a chain up to an end can be generated following a path of easily accessible positions. This introduces a bias which should be compensated by considering a weight factor for each new position chosen (or a product of these factors for a new chain). A similar weight corresponding to reconstructing the old configuration from the new one has also to be calculated. The probability ratios are corrected by introducing the ratio between the new and the old configurational weight factors.		It is usual that many of the accessible configurations have a small probability and only a few ones are probable. In these cases, the simulation is more efficient if the probabilities of the different configurations are previously considered. With this end, the new position for a unit is randomly chosen between a discrete number of possibilities (the neighboring sites in lattice models or a randomly chosen set of positions in other cases), taking into account their Boltzmann probabilities. In the case of polymers, an entirely new part of a chain up to an end can be generated following a path of easily accessible positions. This introduces a bias which should be compensated by considering a weight factor for each new position chosen (or a product of these factors for a new chain). A similar weight corresponding to reconstructing the old configuration from the new one has also to be calculated. The probability ratios are corrected by introducing the ratio between the new and the old configurational weight factors.

	I. Siepman and D. Frenkel, Mol. Phys. 75, 59 1992
			==References==

			1. I. Siepman and D. Frenkel, Mol. Phys. 75, 59 (1992).

Juan: New page: It is usual that many of the accessible configurations have a small probability and only a few ones are probable. In these cases, the simulation is more efficient if the probabilities of t...

2007-06-13T16:14:16Z

New page: It is usual that many of the accessible configurations have a small probability and only a few ones are probable. In these cases, the simulation is more efficient if the probabilities of t...

New page

It is usual that many of the accessible configurations have a small probability and only a few ones are probable. In these cases, the simulation is more efficient if the probabilities of the different configurations are previously considered. With this end, the new position for a unit is randomly chosen between a discrete number of possibilities (the neighboring sites in lattice models or a randomly chosen set of positions in other cases), taking into account their Boltzmann probabilities. In the case of polymers, an entirely new part of a chain up to an end can be generated following a path of easily accessible positions. This introduces a bias which should be compensated by considering a weight factor for each new position chosen (or a product of these factors for a new chain). A similar weight corresponding to reconstructing the old configuration from the new one has also to be calculated. The probability ratios are corrected by introducing the ratio between the new and the old configurational weight factors.

I. Siepman and D. Frenkel, Mol. Phys. 75, 59 1992