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'''Monte Carlo''' is a stochastic [[Computer simulation techniques | computer simulation technique]] frequently used in the study of | |||
soft matter. | |||
{{columns-list|3| | |||
*[[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 | Grand-canonical Monte Carlo]] | |||
*[[Histogram reweighting]] | |||
*[[Importance sampling]] | *[[Importance sampling]] | ||
*[[ | *[[Inverse Monte Carlo]] | ||
*[[Kinetic Monte Carlo]] | |||
*[[Lattice simulations (Polymers)]] | |||
*[[Markov chain]] | *[[Markov chain]] | ||
*[[Monte Carlo | *[[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]] | *[[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== | |||
*[http://links.jstor.org/sici?sici=0162-1459%28194909%2944%3A247%3C335%3ATMCM%3E2.0.CO%3B2-3 Nicholas Metropolis and S. Ulam "The Monte Carlo Method", Journal of the American Statistical Association '''44''' pp. 335-341 (1949)] | |||
==General reading== | |||
*[http://www.oup.com/uk/catalogue/?ci=9780198556459 M. P. Allen and D. J. Tildesley "Computer Simulation of Liquids", Oxford University Press (1989)] Chapter 4. | |||
*[http://molsim.chem.uva.nl/frenkel_smit Daan Frenkel and Berend Smit "Understanding Molecular Simulation: From Algorithms to Applications", Second Edition (2002)] ISBN 0-12-267351-4 Chapter 3. | |||
*[http://www.fz-juelich.de/nic-series/volume23/frenkel.pdf Daan Frenkel "Introduction to Monte Carlo Methods", in ''Computational Soft Matter: From Synthetic Polymers to Proteins'', NIC Series '''Volume 23''' (2004)] | |||
*[http://dx.doi.org/10.2277/0521842387 David P. Landau and Kurt Binder "A Guide to Monte Carlo Simulations in Statistical Physics", 2nd Edition, Cambridge University Press (2005)] | |||
[[category: Computer simulation techniques]] | [[category: Computer simulation techniques]] | ||
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)