The Community for Technology Leaders
RSS Icon
Issue No.05 - September/October (2009 vol.11)
pp: 76-87
<p>In computational studies of complex fluids, Monte Carlo simulations play a valuable role. Such simulations can be divided into two classes: those related to efficient data analysis and those aimed at improving the samples' statistical quality.</p>
Monte Carlo methods, fluid simulation
Gerassimos Orkoulas, "An Overview of Monte Carlo Methods for Fluid Simulation", Computing in Science & Engineering, vol.11, no. 5, pp. 76-87, September/October 2009, doi:10.1109/MCSE.2009.135
1. N. Metropolis et al., "Equation of State Calculations by Fast Computing Machines," J. Chemical Physics, vol. 21, no. 6, 1953, pp. 1087–1092.
2. W. Feller, An Introduction to Probability Theory and its Applications, vol. 1, Wiley, 1968.
3. J.S. Liu, Monte Carlo Strategies in Scientific Computing, Springer, 2001.
4. D. Frenkel and B. Smit, Understanding Molecular Simulation, Academic, 2002.
5. V.I. Manousiouthakis and M.W. Deem, "Strict Detailed Balance is Unnecessary in Monte Carlo Simulations," J. Chemical Physics, vol. 110, no. 6, 1999, pp. 2753–2756.
6. D.P. Landau and K. Binder, A Guide to Monte Carlo Simulations in Statistical Physics, Cambridge, 2000.
7. Z.W. Salsburg et al., "Application of the Monte Carlo Method to the Lattice-Gas model. I. Two-Dimensional Triangular Lattice," J. Chemical Physics, vol. 30, Jan. 1959, pp. 65–72.
8. A.M. Ferrenberg and R.H. Swendsen, "New Monte Carlo Technique for Studying Phase Transitions," Physical Rev. Letters, vol. 61, no. 23, 1988, pp. 2635–2638.
9. A.M. Ferrenberg and R.H. Swendsen, "Optimized Monte Carlo Data Analysis," Physical Rev. Letters, vol. 63, no. 12, 1989, pp. 1195–1198.
10. J.P. Valleau and D.N. Card, "Monte Carlo Estimation of the Free Energy by Multistage Sampling," J. Chemical Physics, vol. 57, no. 12, 1972, pp. 5457–5462.
11. B.A. Berg and T. Neuhaus, "Multicanonical Ensemble: A New Approach to Simulate First-Order Phase Transitions," Physical Rev. Letters, vol. 68, no. 1, 1992, pp. 9–12.
12. J. Lee, "New Monte Carlo Algorithm: Entropic Sampling," Physical Rev. Letters, vol. 71, no. 2, 1993, pp. 211–214.
13. N.B. Wilding, "Computer Simulation of Fluid Phase Transitions," Am. J. Physics, vol. 69, no. 11, 2001, pp. 1147–1155.
14. F. Wang and D.P. Landau, "Efficient Multiple-Range Random Walk to Calculate the Density of States," Physical Rev. Letters, vol. 86, no. 10, 2001, pp. 2050–2053.
15. M.S. Shell, P.G. Debenedetti, and A.Z. Panagiotopoulos, "Generalization of the Wang-Landau Method for Off-Lattice Simulations," Physical Rev. E, vol. 66, no. 5, 2002, pp. 056703.
16. G.R. Smith and A.D. Bruce, "Multicanonical Monte Carlo Study of a Structural Phase Transition," Europhysics Letters, vol. 43, no. 2, 1996, pp. 91–96.
17. M. Fitgerald, R.R. Picard, and R.N. Silver, "Monte Carlo Transition Dynamics and Variance Reduction," J. Statistical Physics, vol. 98, nos. 1-2, 2000, pp. 321–345.
18. J-S. Wang and R.H. Swendsen, "Transition Matrix Monte Carlo," J. Statistical Physics, vol. 106, nos. 1-2, 2002, pp. 245–285.
19. J.R. Errington, "Direct Calculation of Liquid-Vapor Equilibria from Transition Matrix Monte Carlo Simulation," J. Chemical Physics, vol. 118, no. 22, 2003, pp. 9915–9925.
20. E. Marinari and G. Parisi, "Simulated Tempering: A New Monte Carlo Scheme," Europhysics Letters, vol. 19, 1992, pp. 451–458.
21. A.P. Lyubartsev et al., "New Approach to Monte Carlo Calculation of the Free Energy: Method of Expanded Ensembles," J. Chemical Physics, vol. 96, no. 3, 1992, pp. 1776–1783.
22. F.A. Escobedo and J.J. de Pablo, "Expanded Grand Canonical and Gibbs Ensemble Monte Carlo Simulation of Polymers," J. Chemical Physics, vol. 105, no. 10, 1996, pp. 4391–4394.
23. R.H. Swendsen and J-S. Wang, "Replica Monte Carlo Simulation of Spin-Glasses," Physical Rev. Letters, vol. 57, no. 21,986, pp. 2607–2609.
24. K. Hukushima and K. Nemoto, "Exchange Monte Carlo Method and Application to Spin Glass Simulations," J. Physical Soc. Japan, vol. 65, no. 6, 1996, pp. 1604–1608.
25. E. Marinari, G. Parisi, and J.J. Ruiz-Lorenzo, Spin Glasses and Random Fields, A.P. Young ed., World Scientific, 1998.
26. Q. Yan, and J.J. de Pablo, "Hyperparallel Tempering Monte Carlo: Application to the Lennard-Jones Fluid and the Restricted Primitive Model," J. Chemical Physics, vol. 111, no. 21, 1999, pp. 9509–9516.
27. Y. Sugita and Y. Okamoto, "Replica-Exchange Molecular Dynamics Method for Protein Folding," Chemical Physics Letters, vol. 314, nos. 1-2, 1999, pp. 141–151.
28. H. Fukunishi, O. Watanabe, and S. Takada, "On the Hamiltonian Replica Exchange Method for Efficient Sampling of Biomolecular Systems: Application to Protein Structure Prediction," J. Chemical Physics, vol. 116, no. 20, 2002, pp. 9058–9067.
29. E. Lyman, F. Marty Ytreberg, and D.M. Zuckerman, "Resolution Exchange Simulation," Physical Rev. Letters, vol. 96, no. 2, 2006, pp. 28105.
30. C. Dress and W. Krauth, "Cluster Algorithm for Hard Spheres and Related Systems," J. Physics A: Mathematical and General, vol. 28, no. 23, 1995, pp. L597–L601.
31. J. Liu and E. Luijten, "Generalized Geometric Cluster Algorithm for Fluid Simulation," Physical Rev. E, vol. 71, no. 6, 2005, pp. 066701.
32. J. Liu, N.B. Wilding, and E. Luijten, "Simulation of Phase Transitions in Highly Asymmetric Fluid Mixtures," Physical Rev. Letters, vol. 97, no. 11, 2006, pp. 115705.
33. D.M. Tsangaris and J.J. de Pablo, "Bond-Bias Simulation of Phase Equilibria for Stronlgy Associating Fluids," J. Chemical Physics, vol. 101, no. 2, 1994, pp. 1477–1489.
34. B. Chen and J.I. Siepmann, "A Novel Monte Carlo Algorithm for Simulating Strongly Associating Fluids: Applications to Water, Hydrogen Fluoride, and Acetic Acid," J. Physical Chemistry B, vol. 104, no. 36, 2000, pp. 8725–8734.
35. S. Wierzchowski and D.A. Kofke, "A General-Purpose Biasing Scheme for Monte Carlo Simulation of Associating Fluids," J. Chemical Physics, vol. 114, no. 20, 2001, pp. 8752–8762.
36. R. Ren and G. Orkoulas, "Acceleration of Markov Chain Monte Carlo Simulations through Sequential Updating," J. Chemical Physics, vol. 124, no. 6, 2006, pp. 064109.
37. P.H. Peskun, "Optimum Monte-Carlo Sampling Using Markov Chains," Biometrika, vol. 60, no. 3, 1973, pp. 607–712.
38. G. Orkoulas, "Acceleration of Monte Carlo Simulations through Spatial Updating in the Grand Canonical Ensemble," J. Chemical Physics, vol. 127, no. 8, 2007, pp. 084106.
39. C.J. O'Keeffe, R. Ren, and G. Orkoulas, "Spatial Updating Grand Canonical Monte Carlo Algorithms for Fluid Simulation: Generalization to Continuous Potentials and Parallel Implementation," J. Chemical Physics, vol. 127, no. 19, 2007, pp. 194103.
14 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool