Skip to main content

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
Cancel
×
×
Home
  • Home
Chapter
  • Print publication year: 2014
  • Online publication date: November 2014

13 - Monte Carlo simulations at the periphery of physics and beyond

Export citation
Summary

Commentary

In the preceding chapters we described the application of Monte Carlo methods in numerous areas that can be clearly identified as belonging to physics. Although the exposition was far from complete, it should have sufficed to give the reader an appreciation of the broad impact that Monte Carlo studies has already had in statistical physics. A more recent occurrence is the application of these methods in non-traditional areas of physics related research. More explicitly, we mean subject areas that are not normally considered to be physics at all but which make use of physics principles at their core. In some cases physicists have entered these arenas by introducing quite simplified models that represent a ‘physicist's view’ of a particular problem. Often such descriptions are oversimplified, but the hope is that some essential insight can be gained as is the case in many traditional physics studies. (A provocative perspective of the role of statistical physics outside physics has been presented by Stauffer (2004).) In other cases, however, Monte Carlo methods are being applied by non-physicists (or ‘recent physicists’) to problems that, at best, have a tenuous relationship to physics. This chapter is to serve as a brief glimpse of applications of Monte Carlo methods ‘outside’ physics. The number of such studies will surely grow rapidly; and even now, we wish to emphasize that we will make no attempt to be complete in our treatment.

In recent years the simulation of relatively realistic models of proteins has become a ‘self-sufficient’ enterprise. For this reason, such studies will be found in a separate, new chapter (Chapter 14), and in this chapter we will only consider models that are primarily of interest to statistical physicists.

Recommend this book

Email your librarian or administrator to recommend adding this book to your organisation's collection.

A Guide to Monte Carlo Simulations in Statistical Physics
  • Online ISBN: 9781139696463
  • Book DOI: https://doi.org/10.1017/CBO9781139696463
Please enter your name
Please enter a valid email address
Who would you like to send this to *

CAPTCHA *

Skip to the audio challenge
×
References
Adams, C. D., Srolovitz, D. J., and Atzmon, M. (1993), J. Appl. Phys. 74, 1707.
Agrawal, H. (2002), Phys. Rev. Lett. 89, 268702.
Agrawal, H. and Domany, E. (2003), Phys. Rev. Lett. 90, 158102.
Assié, K., Breton, V., Buvat, I., Comtat, C., Jan, S., Krieguer, M., Lazaro, D., Morel, C., Rey, M., Santin, G., Simon, L., Staelens, S., Strul, D., Vieira, J.-M., and van der Walle, R. (2004), Nucl. Instr. and Methods in Phys. Res. A 527, 180.
Bachmann, M. and Janke, W. (2004), J. Chem. Phys. 120, 6779.
Battogtokh, D., Asch, D. K., Case, M. E., Arnold, J., and Schüttler, H.-B. (2002), Proc. Natl Acad. Sci. (USA) 99, 16904.
Chaumont, P., Gnanou, Y., Hild, G., and Rempp, P. (1985), Macromol. Chem. 186, 2321.
Chen, N., Glazier, J. A., Izaguirre, J. A., and Alber, M. S. (2007), Comput. Phys. Commun. 176, 670.
Chowdhury, D., Santen, L., and Schadschneider, A. (2000), Phys. Rep, 329, 199.
Cont, R. and Bouchaud, J. P (2000), Macroeconomic Dynamics 4, 170.
Cuticchia, A. J., Arnold, J., and Timberlake, W. E. (1992), Genetics 132, 591.
Czirók, A. and Vicsek, T. (2000), Physica A 322, 17.
de Oliveira, S. M., de Oliveira, P. M. C., and Stauffer, D. (2003), Physica A 322, 521.
Derrida, B., Manrubia, S. C., and Zanette, D. H. (2000), Physica A 281, 1.
Deutsch, H.-P. (2002), Derivatives and Internal Models, 2nd edn. (Palgrave, New York).
Dill, K. A. (1985), Biochemistry 24, 1501.
Elliott, J. and Hancock, B., eds. (2006), MRS Bulletin 31.
Ertl, G. (1990), Adv. Catalysis 37, 213.
Fasolino, A., Los, J. H., and Katsnelson, M. I. (2007), Nature Mater. 6, 858.
Gilks, W. R., Richardson, S., and Spiegelhalter, D. J. (eds.) (1996), Markov Chain Monte Carlo in Practice (Chapman and Hall, London).
Graner, F. and Glazier, J. A. (1992), Phys. Rev. Lett. 69, 2013.
Guclu, H., Korniss, G., Novotny, M. A., Toroczkai, Z., and Rácz, Z. (2006), Phys. Rev. E 73, 066115.
Hammel, C. and Paul, W. B. (2002), Physica A 313, 640.
Hastings, W. (1970), Biometrika 57, 97.
Hitchcock, D. H. (2003), Amer. Stat. 57, 254.
Hsu, H.-P., Mehra, V., Nadler, W., and Grassberger, P. (2003a), Phys. Rev. E 68, 021113.
Hsu, H.-P., Mehra, V., Nadler, W., and Grassberger, P. (2003b), J. Chem. Phys. 118, 444.
Imbiehl, R. (1993), Progr. Surf. Sci. 44, 185.
Ishisaki, Y., Maeda, Y., Fujimoto, R., Ozaki, M., Ebisawa, K., Takahashi, T., Ueda, Y., Ogasaka, Y., Ptak, A., Mukai, K., Hamaguchi, K., Hirayama, M., Kotani, T., Kubo, H., Shibata, R., Ebara, M., Furuzawa, A., Izuka, R., Inoue, H., Mori, H., Okada, S., Yokoyama, Y., Matsumoto, H., Nakajima, H., Yamaguchi, H., Anabuki, N., Tawa, N., Nagai, M., Katsuda, S., Hayashida, K., Bamba, A., Miller, E. D., Sato, K., and Yamasaki, N.Y. (2007), Publ. Astron. Soc. Japan 59, S113.
Jäckel, P. (2002), Monte Carlo Methods in Finance (Wiley, Chichester).
John, A. and Sommer, J.-U. (2008), Macromol. Theory Simul. 17, 274.
Johnson, A. F. and O’Driscoll, K. F. (1984), Eur. Polym. J. 20, 979
Johnson, J. K. (1999), in Monte Carlo Methods in Chemical Physics, eds. Ferguson, D. M., Siepmann, J. I., and Truhlar, D. G. (J. Wiley & Sons, New York), p. 461.
Jorgensen, W. L. and Tirado-Rives, J. (1996), J. Phys. Chem. 100, 14508.
Kopelman, R. (1989), in The Fractal Approach to Heterogeneous Chemistry, ed. Avnir, D. (J. Wiley & Sons, New York), p. 295.
Kou, S. C., Oh, J., and Wong, W. H. (2006), J. Chem. Phys. 124, 244 903.
Kumpula, J. M., Onnela, J.-P., Saramäki, J., Kaski, K., and Kertész, J. (2007), Phys. Rev. Lett. 99, 228 701.
Lattmann, E. E., Fiebig, K. M., and Dill, K. A. (1994), Biochemistry 33, 6158.
Lau, K. F., and Dill, K. A. (1989), Macromolecules 22, 3986.
Leal, A., Sánchez-Doblado, F., Perucha, M., Carrasco, E., and Rincón, M. (2004), Comput. in Sci. and Eng. 6, 60.
Lesh, N., Mitzenmacher, M., and Whitesides, S. (2003), in Proceedings of the 7th Annual International Conference on Research in Computational Molecular Biology (ACM Press, New York), p. 188.
Liu, J. (2001), Monte Carlo Strategies in Scientific Computing (Springer, New York).
Loscar, E. and Albano, E. V. (2003), Rep. Progr. Phys. 66, 1343.
McLeish, D. L. (2005), Monte Carlo Simulation and Finance (Wiley, Hoboken).
Malec, H. A. (1971), Microelectronics and Reliability 10, 339.
Marro, J. and Dickman, R. (1999), Nonequilibrium Phase Transitions and Critical Phenomena (Cambridge University Press, Cambridge).
Mücke, A., Engel, R., Rachen, J. P., Protheroe, R. J., and Stanev, T. (2000), Comp. Phys. Commun. 124, 290.
Mustonen, V. and Rajesh, R. (2003), J. Phys. A: Math and General 36, 6651.
Nagase, F. and Watanabe, S. (2006), Adv. Space Res. 38, 2737.
Nagel, K. and Schreckenberg, M. (1992), J. Physique I 2, 2221.
Newman, M. E. J. and Girvan, M. (2004), Phys. Rev. E 69, 026113.
Northrup, S. H. and McCammon, J. A. (1980), Biopol. 19, 1001.
Onnela, J.-P., Saramäki, J., Hyvönen, J., Szabó, G., Lazer, D., Kaski, K., Kertész, J., and Barabási, A.-L. (2007), PNAS 104, 7332.
Pitfield, D. E. and Jerrard, E. A. (1999), J. Air Trans. Manag. 5, 185.
Pitfield, D. E., Brooks, A. S., and Jerrard, E. A. (1998), J. Air Trans. Manag. 4, 3.
Richardson, R. B. and Dubeau, J. (2003), Rad. Prot. Dosim. 103, 5.
Shirinifard, A., Glazier, J. A., Swat, M., Gens, J. S., Family, F., Hiang, Y., and Grossniklaus, H. E. (2012), PLoS Comput. Biol. 8, e1002440.
Stanley, H. E., Amaral, L. A. N., Canning, D., Gopikrishnan, P., Lee, Y., and Liu, Y. (1999), Physica A 269, 156.
Stanley, H. E., Ausloos, M., Kertesz, J., Mantegna, R. N., Scheinkman, J. A., and Takayasu, H. (2003), The Proceedings of the International Econophysics Conference, Physica A 324.
Stauffer, D. (2001), Adv. Complex Systems 4, 19.
Stauffer, D. (2002), Comput. Phys. Commun. 146, 93.
Stauffer, D. (2003), Comput. in Sci. and Eng. May–June, 5, 71.
Stauffer, D. (2004), Physica A 336, 1.
Stauffer, D., Moss de Oliveira, S., de Oliveira, P. M. C., and Martins, Sá. (2006), Biology, Sociology, Geology by Computational Physicists (Elsevier, Amsterdam).
Sznajd-Weron, K. and Sznajd, J. (2000), Int. J. Mod. Phys. C 11, 1239.
Tang, S. H. and Ong, P. P. (1988), Appl. Acoustics 23, 263.
Toma, L. and Toma, S. (1996), Protein Sci. 5, 147.
Waldeer, K. T. (2003), Comput. Phys. Commun. 156, 1.
Watanabe, S., Nagase, F., Takahashi, T., Sako, M., Kahn, S. M., Ishida, M., Ishisaki, Y., Kohmura, T., and Paerels, F. (2004), 22nd Texas Symposium on Relativistic Astrophysics, SLAC-PUB-11350.
Watts, D. J. and Strogatz, S. H. (1998), Nature 393, 440.
Wüst, T. and Landau, D. P. (2008), Comput. Phys. Comm. 179, 124.
Yip, S. (ed.) (2005), Handbook of Materials Modeling (Springer, Berlin).
Yip, M. H. and Carvalho, M. J. (2007), Comput. Phys. Commun. 177, 965.
Yu, Y., Dong, W., Altimus, C., Tang, X., Griffith, J., Morello, M., Dudek, L., Arnold, J., and Schüttler, H.-B. (2007), PNAS 104, 2809.
Zhang, J., Kou, S.C., and Liu, J. (2007), J. Chem. Phys. 126, 225 101.
Ziff, R., Gulari, E., and Barshad, Y. (1986) Phys. Rev. Lett. 56, 2553.
Cancel
Confirm
×