Monte Carlo: Difference between revisions
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*[[Gibbs ensemble Monte Carlo]] | *[[Gibbs ensemble Monte Carlo]] | ||
*[[Glauber transition probabilities]] also known as: Barkers method | *[[Glauber transition probabilities]] also known as: Barkers method | ||
*[[Grand canonical Monte Carlo | Grand-canonical Monte Carlo]] | |||
*[[Histogram reweighting]] | *[[Histogram reweighting]] | ||
*[[Importance sampling]] | *[[Importance sampling]] | ||
*[[Inverse Monte Carlo]] | *[[Inverse Monte Carlo]] | ||
*[[Kinetic Monte Carlo]] | |||
*[[Lattice simulations (Polymers)]] | *[[Lattice simulations (Polymers)]] | ||
*[[Markov chain]] | *[[Markov chain]] | ||
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*[[Metropolis Monte Carlo]] | *[[Metropolis Monte Carlo]] | ||
*[[Metropolis-Hastings Monte Carlo]] | *[[Metropolis-Hastings Monte Carlo]] | ||
*[[Monte Carlo in the microcanonical ensemble]] | *[[Monte Carlo in the microcanonical ensemble]] | ||
*[[Monte Carlo reptation moves]] | *[[Monte Carlo reptation moves]] | ||
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*[[RIS Metropolis Monte Carlo]] | *[[RIS Metropolis Monte Carlo]] | ||
*[[Simulated annealing]] | *[[Simulated annealing]] | ||
*[[Tethered Monte Carlo]] | |||
*[[Umbrella sampling]] | *[[Umbrella sampling]] | ||
*[[Wang-Landau method]] | *[[Wang-Landau method]] | ||
*[[Waste recycling Monte Carlo]] | |||
}} | }} | ||
==Historical papers== | ==Historical papers== | ||
Latest revision as of 19:25, 1 February 2012
Monte Carlo is a stochastic computer simulation technique frequently used in the study of soft matter.
- Basin-hopping Monte Carlo
- Cluster algorithms
- Concerted rotation algorithm
- Configurational bias Monte Carlo
- Constant-pressure Monte Carlo
- Detailed balance
- End-bridging Monte Carlo
- Fragment regrowth Monte Carlo
- Gibbs-Duhem integration
- Gibbs ensemble Monte Carlo
- Glauber transition probabilities also known as: Barkers method
- Grand-canonical Monte Carlo
- Histogram reweighting
- Importance sampling
- Inverse Monte Carlo
- Kinetic Monte Carlo
- Lattice simulations (Polymers)
- Markov chain
- Mayer sampling Monte Carlo
- Metropolis Monte Carlo
- Metropolis-Hastings Monte Carlo
- Monte Carlo in the microcanonical ensemble
- Monte Carlo reptation moves
- Overlapping distribution method
- Parrinello-Rahman barostat
- Phase switch Monte Carlo
- Quantum Monte Carlo
- Random numbers
- Recoil growth
- Reverse Monte Carlo
- RIS Metropolis Monte Carlo
- Simulated annealing
- Tethered Monte Carlo
- Umbrella sampling
- Wang-Landau method
- Waste recycling Monte Carlo
Historical papers[edit]
General reading[edit]
- M. P. Allen and D. J. Tildesley "Computer Simulation of Liquids", Oxford University Press (1989) Chapter 4.
- Daan Frenkel and Berend Smit "Understanding Molecular Simulation: From Algorithms to Applications", Second Edition (2002) ISBN 0-12-267351-4 Chapter 3.
- Daan Frenkel "Introduction to Monte Carlo Methods", in Computational Soft Matter: From Synthetic Polymers to Proteins, NIC Series Volume 23 (2004)
- David P. Landau and Kurt Binder "A Guide to Monte Carlo Simulations in Statistical Physics", 2nd Edition, Cambridge University Press (2005)