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7 - Reweighting methods

Published online by Cambridge University Press:  24 November 2021

David Landau  and
Kurt Binder
David Landau
Affiliation:
University of Georgia
Kurt Binder
Affiliation:
Johannes Gutenberg Universität Mainz, Germany
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Summary

One longstanding limitation on the resolution of Monte Carlo simulations near phase transitions has been the need to perform many runs to precisely characterize peaks in response functions such as the specific heat. Dramatic improvements have become possible with the realization that entire distributions of properties, not just mean values, can be useful; in particular, they can be used to predict the behavior of the system at a temperature other than that at which the simulation was performed. There are several different ways in which this may be done. The reweighting may be done after a simulation is complete or it may become an integral part of the simulation process itself. The fundamental basis for this approach is the realization that the properties of the systems will be determined by a distribution function in an appropriate ensemble.

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A Guide to Monte Carlo Simulations in Statistical Physics , pp. 326 - 364
Publisher: Cambridge University Press
Print publication year: 2021

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References

Adler, J. (1983), J. Phys. A 16, 3585.Google Scholar
Baillie, C. F., Gupta, R., Hawick, K. A., and Pawley, G. S. (1992), Phys. Rev. B 45, 10438.CrossRefGoogle Scholar
Barash, L. Yu., Fadeeva, M. A., and Shchur, L. N. (2017), Phys. Rev. E 96, 043307.Google Scholar
Beale, P. D. (1996), Phys. Rev. Lett. 76, 78.Google Scholar
Belardinelli, R. E. and Pereyra, V. D. (2007a), J. Chem. Phys. 127, 184105.CrossRefGoogle Scholar
Belardinelli, R. E. and Pereyra, V. D. (2007b), Phys. Rev. E 75, 046701.Google Scholar
Bennett, C. H. (1976), J. Comput. Phys. 22, 245.CrossRefGoogle Scholar
Berg, B. and Neuhaus, T. (1991), Phys. Lett. B 267, 249.Google Scholar
Berg, B. and Neuhaus, T. (1992), Phys. Rev. Lett. 68, 9.Google Scholar
Berg, B. A. (1996), J. Stat. Phys. 82, 343.Google Scholar
Berg, B. A. (1997), in Proceedings of the International Conference on Multiscale Phenomena and Their Simulations (Bielefeld, Oct. 1996), eds. Karsch, F., Monien, B., and Satz, H. (World Scientific, Singapore), p. 137.Google Scholar
Berg, B. A., Hansmann, U., and Neuhaus, T. (1993), Phys. Rev. B 47, 497.Google Scholar
Binder, K. (1982), Phys. Rev. A 25, 1699.CrossRefGoogle Scholar
Binder, K. and Hohenberg, P. C. (1972), Phys. Rev. B 6, 3461.Google Scholar
Binder, K. and Hohenberg, P. C. (1974), Phys. Rev. B 9, 2194.Google Scholar
Binder, K. and Landau, D. P. (1984), Phys. Rev. Lett. 52, 318.Google Scholar
Binder, K. and Luijten, E. (2001), Physics Reports 344, 179.Google Scholar
Blöte, H. W. J. and Kamieniarz, G. (1993), Physica A 196, 455.CrossRefGoogle Scholar
Blöte, H. W. J., Compagner, A., Croockewit, J. H., Fonk, Y. T. J. C., Heringa, J. R., Hoogland, A., Smit, T. S., and van Willigen, A. L. (1989a), Physica A 161, 1.Google Scholar
Blöte, H. W. J., de Bruin, J., Compagner, A., Croockewit, J. H., Fonk, Y. T. J. C., Heringa, J. R., Hoogland, A., and van Willigen, A. L. (1989b), Europhys. Lett. 10, 105.CrossRefGoogle Scholar
Blöte, H. W. J., Luijten, E., and Heringa, J. R. (1995), J. Phys. A 28, 6289.CrossRefGoogle Scholar
Butera, P. and Comi, M. (1997), Phys. Rev. B 56, 8212.Google Scholar
Chen, K., Ferrenberg, A. M., and Landau, D. P. (1993), Phys. Rev. B 48, 239.Google Scholar
Dayal, P., Trebst, S., Wessel, S., Wurtz, D., Troyer, M., Sabhapandit, S., and Coppersmith, S. N. (2004), Phys. Rev. Lett. 92, 097201.Google Scholar
de Oliveira, P. M. C., Penna, T. J. P., and Herrmann, H. J. (1996), Braz. J. Phys. 26, 677.Google Scholar
Deng, Y., Blöte, H. W. J., and Nightingale, M. P. (2005), Phys. Rev. E 72, 018128.Google Scholar
Diehl, H. W. and Dietrich, S. (1981), Phys. Rev. B 24, 2878.Google Scholar
Diehl, H. W. and Shpot, M. (1994), Phys. Rev. Lett. 73, 3431.Google Scholar
Diehl, H. W. and Shpot, M. (1998), Nucl. Phys. B 528, 469.CrossRefGoogle Scholar
Ferrenberg, A. M. (1991), in Computer Simulation Studies in Condensed Matter Physics III, eds. Landau, D. P., Mon, K. K., and Schüttler, H.-B. (Springer-Verlag, Heidelberg), p. 30.CrossRefGoogle Scholar
Ferrenberg, A. M. and Landau, D. P. (1991), Phys. Rev. B 44, 5081.CrossRefGoogle Scholar
Ferrenberg, A. M. and Swendsen, R. H. (1988), Phys. Rev. Lett. 61, 2635.CrossRefGoogle Scholar
Ferrenberg, A. M. and Swendsen, R. H. (1989), Phys. Rev. Lett. 63, 1195.CrossRefGoogle Scholar
Ferrenberg, A. M., Xu, J., and Landau, D. P. (2018), Phys. Rev. E 97, 043301.CrossRefGoogle Scholar
Fisher, M. E. (1995), J. Phys. A 28, 6323.Google Scholar
Frenkel, D. and Smit, B. (2001), Understanding Molecular Simulation: From Algorithms to Applications, 2nd ed. (Academic Press, New York).Google Scholar
Hasenbusch, M. (2010), Phys. Rev. B 82, 174433.Google Scholar
Hasenbusch, M. (2011), Phys. Rev. B 84, 134405.Google Scholar
Hukusima, K. and Nemoto, K. (1996), J. Phys. Soc. Japan 65, 1604.Google Scholar
Jain, T. S. and de Pablo, J. J. (2002), J. Chem. Phys. 116, 7238.CrossRefGoogle Scholar
Jain, T. S. and de Pablo, J. J. (2003), J. Chem. Phys. 118, 4226.Google Scholar
Janke, W. (1992), in Dynamics of First Order Transitions, eds. Herrmann, H. J., Janke, W., and Karsch, F. (World Scientific, Singapore), p. 365.Google Scholar
Janke, W. (1997), in New Directions in Statistical Physics, eds. Hu, C.-K. and Leung, K.-T. (Elsevier, Amsterdam), p. 164.Google Scholar
Janke, W. and Kappler, S. (1995), Phys. Rev. Lett. 74, 212.Google Scholar
Koller, W., Prull, A., and Evertz, H. G. (2003), Phys. Rev. B 67, 104432.Google Scholar
Krech, M. and Landau, D. P. (1996), Phys. Rev. E 53, 4414.Google Scholar
Landau, D. P. and Binder, K. (1990), Phys. Rev. B 41, 4633.CrossRefGoogle Scholar
Lee, Y. and Choi, M. Y. (1994), Phys. Rev. E 50, 4420.CrossRefGoogle Scholar
LeGuillou, J.-C. and Zinn-Justin, J. (1980), Phys. Rev. B 21, 3976.Google Scholar
Li, Y.-W., Wüst, T., Landau, D. P., and Lin, H.-Q. (2007), Comp. Phys. Commun. 177, 524.Google Scholar
Liang, F. (2006), J. Stat. Phys. 122, 511.Google Scholar
Liang, F., Liu, C., and Carroll, R. J. (2007), J. Amer. Statist. Assoc. 102, 305.Google Scholar
Liu, A. J. and Fisher, M. E. (1989), Physica A 156, 35.CrossRefGoogle Scholar
Liu, A. J. and Fisher, M. E. (1990), J. Stat. Phys. 58, 431.CrossRefGoogle Scholar
Livet, F. (1991), Europhys. Lett. 16, 139.CrossRefGoogle Scholar
Lyubartsev, A. P., Martsinovski, A. A., Shevkunov, S. V., and Vorentsov-Velyaminov, P. N. (1992), J. Chem. Phys. 96, 1776.Google Scholar
MacDowell, L. G., Virnau, P., Müller, M., and Binder, K. (2004), J. Chem. Phys. 120, 5293.Google Scholar
Marinari, E. and Parisi, G. (1992), Europhys. Lett. 19, 451.Google Scholar
Mognetti, B. M., Yelash, L., Virnau, P., Paul, W., Binder, K., Müller, M., and MacDowell, L. G. (2008), J. Chem. Phys. 128, 104501.Google Scholar
Mon, K. K. (1985), Phys. Rev. Lett. 54, 2671.Google Scholar
Müller, M. and de Pablo, J. J. (2006), in Computer Simulations in Condensed Matter: From Materials to Chemical Biology, eds. Ferrario, M., Ciccotti, G., and Binder, K. (Springer, Heidelberg), vol. 1, p. 67.Google Scholar
Müller, M., Binder, K., and Oed, W. (1995), J. Chem. Soc. Faraday Trans. 28, 8639.Google Scholar
Nickel, B. G. and Rehr, J. J. (1990), J. Stat. Phys. 61, 11.Google Scholar
Nightingale, M. P. and Blöte, H. W. J. (1988), Phys. Rev. Lett. 60, 1662.CrossRefGoogle Scholar
Novotny, M. A. (1991), Nucl. Phys. B Proc. Suppl. 20, 122.Google Scholar
Pawley, G. S., Swendsen, R. H., Wallace, D. J., and Wilson, K. G. (1984), Phys. Rev. B 29, 4030.Google Scholar
Pelissetto, A. and Vicari, E. (2002), Phys. Rep. 368, 549.Google Scholar
Rathore, N., Knotts, T. A., and de Pablo, J. J. (2003), J. Chem. Phys. 118, 4285.CrossRefGoogle Scholar
Reuhl, M. (1997), Diplomarbeit (University of Mainz, unpublished).Google Scholar
Rosengren, A. (1986), J. Phys. A 19, 1709.Google Scholar
Ruge, C., Dunkelmann, S., and Wagner, F. (1992), Phys. Rev. Lett. 69, 2465.Google Scholar
Saito, M. and Matsumoto, H. (2009), in Monte Carlo and Quasi-Monte-Carlo Methods 2006, ed. Keller, A., Heinrich, S., and Niederreiter, H. (Springer, Berlin), p. 589.Google Scholar
Salman, Z. and Adler, J. (1998), Int. J. Mod. Phys. C 9, 195.CrossRefGoogle Scholar
Schnabel, S., Seaton, D. T., Landau, D. P., and Bachmann, M. (2011), Phys. Rev. E 84, 011127.Google Scholar
Schneider, S., Mueller, M., and Janke, W. (2017), Comput. Phys Commun. 216, 1.Google Scholar
Schulz, B. J., Binder, K., and Mueller, M. (2002), Int. J. Mod. Phys. C 13, 477.Google Scholar
Schulz, B. J., Binder, K., Mueller, M., and Landau, D. P. (2003), Phys. Rev. E 67, 067102.Google Scholar
Shell, M. S., Debenedetti, P. G., and Panagiotopoulos, A. Z. (2002), Phys. Rev. E 66, 056703.Google Scholar
Shing, K. S. and Gubbins, K. E. (1983), Mol. Phys. 49, 1121.Google Scholar
Torrie, G. M. and Valleau, J. P. (1977), J. Comput. Phys. 23, 187.Google Scholar
Tröster, A. and Dellago, C. (2005), Phys. Rev. E 71, 066705.Google Scholar
Troyer, M., Sabhapandit, S., and Coppersmith, S. N. (2003a), Phys. Rev. Lett. 92, 097201.Google Scholar
Troyer, M., Wessel, S., and Alet, F. (2003b), Phys. Rev. Lett. 90, 120201.Google Scholar
Tsai, S.-H., Wang, F., and Landau, D. P. (2007), Phys. Rev. E 75, 061108.Google Scholar
Vendruscolo, M., Rovere, M., and Fasolino, A. (1992), Europhys. Lett. 20, 547.Google Scholar
Virnau, P. and Müller, M. (2004), J. Chem. Phys. 120, 10925.Google Scholar
Vogel, V., Li, Y. W., Wüst, T., and Landau, D. P. (2013), Phys. Rev. Lett. 110, 210603.Google Scholar
Vogel, V., Li, Y. W., Wüst, T., and Landau, D. P. (2014), Phys. Rev. E 90, 023302.Google Scholar
Wang, F. and Landau, D. P. (2001a), Phys. Rev. Lett. 86, 2050.Google Scholar
Wang, F. and Landau, D. P. (2001b), Phys. Rev. E 64, 056101.Google Scholar
Wang, J.-S., Tay, T. K. and Swendsen, R. H. (1999), Phys. Rev. Lett. 82, 476.CrossRefGoogle Scholar
Wansleben, S. and Landau, D. P. (1991), Phys. Rev. B 43, 6006.Google Scholar
Yamaguchi, C. and Kawashima, N. (2002), Phys. Rev. E 65, 056710.Google Scholar
Yan, Q. and de Pablo, J. J. (2003), Phys. Rev. Lett. 90, 035701.CrossRefGoogle Scholar
Yin, J. and Landau, D. P. (2012), Comput. Phys. Commun. 183, 1568.Google Scholar
Zhou, C. and Bhatt, R. H. (2005), Phys. Rev. E 72, 025701.Google Scholar
Zhou, C., Schulthess, T. C., Torbrügge, S., and Landau, D. P. (2006), Phys. Rev. Lett. 96, 120201.Google Scholar
Zierenberg, J., Marenz, M., and Janke, W. (2013), Comput. Phys. Commun. 184, 1155.Google Scholar
Zinn-Justin, J. (2001), Physics Reports 344, 159.Google Scholar

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  • Reweighting methods
  • David Landau, University of Georgia, Kurt Binder, Johannes Gutenberg Universität Mainz, Germany
  • Book: A Guide to Monte Carlo Simulations in Statistical Physics
  • Online publication: 24 November 2021
  • Chapter DOI: https://doi.org/10.1017/9781108780346.008
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  • Reweighting methods
  • David Landau, University of Georgia, Kurt Binder, Johannes Gutenberg Universität Mainz, Germany
  • Book: A Guide to Monte Carlo Simulations in Statistical Physics
  • Online publication: 24 November 2021
  • Chapter DOI: https://doi.org/10.1017/9781108780346.008
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  • Reweighting methods
  • David Landau, University of Georgia, Kurt Binder, Johannes Gutenberg Universität Mainz, Germany
  • Book: A Guide to Monte Carlo Simulations in Statistical Physics
  • Online publication: 24 November 2021
  • Chapter DOI: https://doi.org/10.1017/9781108780346.008
Available formats
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