Guide to Practical Work with the Monte Carlo Method

Part of the Springer Series in Solid-State Sciences book series (SSSOL, volume 80)


The guide is structured such that we proceed from the “easy” simulation methods and algorithms to the more sophisticated. For each method the algorithms are presented by the technique of stepwise refinement We first present the idea and the basic outline. Prom then on we proceed by breaking up the larger logical and algorithmic structures into smaller ones, until we have reached the level of single basic statements. Sometimes we may elect not to go to such a depth and the reader is asked to fill in the gaps.


Random Walk Ising Model Random Number Generator Importance Sampling Phase Transition Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 3.1
    Transputer Reference Manual (Inmos Ltd., Bristol 1986)Google Scholar
  2. 3.2
    Transputer Development System (Inmos Ltd., Bristol 1986)Google Scholar
  3. 3.3
    K. Bowler, A.D. Bruce, R.D. Kenway, G.S. Pawley, D.J. Wallace: Phys. Today 10, 40 (1987)CrossRefGoogle Scholar
  4. 3.4
    Occam Programming Language (Prentice-Hall, Englewood Cliffs, NJ 1984)Google Scholar
  5. 3.5
    R. Steinmetz: Occam 2 (Hüthig Verlag, Heidelberg 1987)Google Scholar
  6. 3.6
    G. Jones: Programming in OCCAM (Prentice-Hall, Englewood Cliffs, NJ 1987)zbMATHGoogle Scholar
  7. 3.7
    K.C. Bowler, R.D. Kenway, G.S. Pawley, D. Roweth: Occam 2 Programming Language (Prentice-Hall, Englewood Cliffs, NJ 1984)Google Scholar
  8. 3.8
    W. Paul, D.W. Heermann, R.C. Desai: J. Comp. Phys. 82, 487 (1989)MathSciNetADSzbMATHCrossRefGoogle Scholar
  9. 3.9
    R.C. Desai, D.W. Heermann, K. Binder: J. Stat. Phys. 53, 795 (1988)MathSciNetADSCrossRefGoogle Scholar
  10. 3.10
    W. Paul, D.W. Heermann, R.C. Desai: Mainz Preprint 87/46 (1987)Google Scholar
  11. 3.11
    D. Knuth: The Art of Computer Programming, Vol. 2 (Addison-Wesley, Reading, MA 1969)zbMATHGoogle Scholar
  12. 3.12
    D.W. Heermann: Computer Simulation Methods in Theoretical Physics (Springer, Berlin, Heidelberg 1986)CrossRefGoogle Scholar
  13. 3.13
    M.P. Allen, D.J. Tildesley: Computer Simulation of Liquids (Clarendon, Oxford 1987)zbMATHGoogle Scholar
  14. 3.14
    M.H. Kalos, P.A. Whitlock: Monte Carlo Methods, Vol. 1 (Wiley, New York 1986)zbMATHCrossRefGoogle Scholar
  15. 3.15.
    J.H. Ahrens, U. Dieter: Pseudo Random Numbers (Wiley, New York) in preparationGoogle Scholar
  16. 3.16
    D.H. Lehmer: In Proc. 2nd Symp. on Large-Scale Digital Computing Machinery, Vol. 142 (Harvard University Press, Cambridge, MA 1951)Google Scholar
  17. 3.17
    A. Milchev, K. Binder, D.W. Heermann: Z. Phys. B 63, 521 (1986)ADSCrossRefGoogle Scholar
  18. 3.18
    H.E. Stanley: J. Stat. Phys. 36, 843 (1984)ADSCrossRefGoogle Scholar
  19. 3.19
    L. Onsager: Phys. Rev. 65, 117 (1944)MathSciNetADSzbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  1. 1.Institut für PhysikJohannes Gutenberg UniversitätMainzGermany
  2. 2.Institut für Theoretische PhysikUniversität HeidelbergHeidelbergGermany

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