Monte Carlo: Difference between revisions
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==General reading== | ==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://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://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)] | *[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]] | ||
Revision as of 16:39, 7 April 2010
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
- Histogram reweighting
- Importance sampling
- Inverse Monte Carlo
- Lattice simulations (Polymers)
- Markov chain
- Metropolis Monte Carlo
- Metropolis-Hastings Monte Carlo
- Grand-canonical Monte Carlo
- Monte Carlo in the microcanonical ensemble
- Monte Carlo reptation moves
- Overlapping distribution method
- Parrinello-Raman barostat
- Phase switch Monte Carlo
- Quantum Monte Carlo
- Random numbers
- Recoil growth
- Reverse Monte Carlo
- RIS Metropolis Monte Carlo
- Simulated annealing
- Umbrella sampling
- Wang-Landau method
Historical papers
General reading
- 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)