Monte Carlo molecular modelling is the application of Monte Carlo methods to molecular problems. These problems can also be modelled by the molecular dynamics method. The difference is that this approach relies on equilibrium statistical mechanics rather than molecular dynamics. Instead of trying to reproduce the dynamics of a system, it generates states according to appropriate Boltzmann distribution. Thus, it is the application of the Metropolis Monte Carlo simulation to molecular systems. It is therefore also a particular subset of the moregeneral Monte Carlo method in statistical physics.
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| - Monte-Carlo-Modellierung molekularer Systeme (de)
- Monte Carlo molecular modeling (en)
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| - In der Monte-Carlo-Modellierung molekularer Systeme werden molekulare Systeme durch Monte-Carlo-Simulationen untersucht. In der statistischen Physik wird siefür eine Modellierung von Gleichgewichtseigenschaftenauf atomarer bis molekularer Ebene verwendet und kann in Einzelfällen eine Beschleunigung von einem Faktor von über 1010 im Vergleich zu Molekulardynamik-Simulationen erzielen. (de)
- Monte Carlo molecular modelling is the application of Monte Carlo methods to molecular problems. These problems can also be modelled by the molecular dynamics method. The difference is that this approach relies on equilibrium statistical mechanics rather than molecular dynamics. Instead of trying to reproduce the dynamics of a system, it generates states according to appropriate Boltzmann distribution. Thus, it is the application of the Metropolis Monte Carlo simulation to molecular systems. It is therefore also a particular subset of the moregeneral Monte Carlo method in statistical physics. (en)
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| - In der Monte-Carlo-Modellierung molekularer Systeme werden molekulare Systeme durch Monte-Carlo-Simulationen untersucht. In der statistischen Physik wird siefür eine Modellierung von Gleichgewichtseigenschaftenauf atomarer bis molekularer Ebene verwendet und kann in Einzelfällen eine Beschleunigung von einem Faktor von über 1010 im Vergleich zu Molekulardynamik-Simulationen erzielen. Sie kann sowohl die potentielle Energie bestimmen als auch eine statistische Aussage über die Lage von Atomen liefern und auch Zustandsgrößen der Boltzmann-Statistik bestimmen. Monte-Carlo und Molekulardynamik sind die häufigsten Modellierungen von Fluiden auf atomarer Ebene. Die empirischen Kraftfelder, die dafür verwendet werden, stammen sowohl von Ab-initio-Rechnungen als auch von Experimenten und werden sowohl für die Molekulardynamik als auch für die molekulare Monte-Carlo-Methode verwendet. Einige Programmsysteme verwenden Mehr-Atom-Modelle („Coarse-grained model“), sie wenden die molekulare Monte-Carlo-Methode nicht auf einzelne Atome an, sondern auf den Schwerpunkt von Atomgruppen oder ganzen Molekülen.Methoden, die zur Modellierung molekularer Systeme herangezogen werden sind die Kinetische Monte-Carlo-Methode und die Quanten-Monte-Carlo-Methode. (de)
- Monte Carlo molecular modelling is the application of Monte Carlo methods to molecular problems. These problems can also be modelled by the molecular dynamics method. The difference is that this approach relies on equilibrium statistical mechanics rather than molecular dynamics. Instead of trying to reproduce the dynamics of a system, it generates states according to appropriate Boltzmann distribution. Thus, it is the application of the Metropolis Monte Carlo simulation to molecular systems. It is therefore also a particular subset of the moregeneral Monte Carlo method in statistical physics. It employs a Markov chain procedure in order to determine a new state for a system from a previous one. According to its stochastic nature, this new state is accepted at random. Each trial usually counts asa move. The avoidance of dynamics restricts the method to studies of static quantities only, but the freedom to choose moves makes the method very flexible. These moves must only satisfy a basic condition ofbalance in order for the equilibrium to be properly described, but detailed balance, a stronger condition,is usually imposed when designing new algorithms. An additional advantage is that some systems, such as the Ising model, lack a dynamical description and are only defined by an energy prescription; for these the Monte Carlo approach is the only one feasible. The great success of this method in statistical mechanics has led to various generalizations such as the method of simulated annealing for optimization, in which a fictitious temperature is introduced and then gradually lowered. A range of software packages have been developed specifically for the use of the Metropolis Monte Carlo method on molecular simulations. These include:
* BOSS
* CP2K
* MCPro
* Sire
* ProtoMS
* Faunus (en)
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