Journal of Statistical Physics

, Volume 58, Issue 1–2, pp 159–183 | Cite as

Monte Carlo generation of self-avoiding walks with fixed endpoints and fixed length

  • N. Madras
  • A. Orlitsky
  • L. A. Shepp


We propose a new class of dynamic Monte Carlo algorithms for generating self-avoiding walks uniformly from the ensemble with fixed endpoints and fixed length in any dimension, and prove that these algorithms are ergodic in all cases. We also prove the ergodicity of a variant of the pivot algorithm.

Key words

Self-avoiding walk self-avoiding polygon Monte Carlo ergodicity pivot algorithm 


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Copyright information

© Plenum Publishing Corporation 1990

Authors and Affiliations

  • N. Madras
    • 1
  • A. Orlitsky
    • 2
  • L. A. Shepp
    • 2
  1. 1.Department of MathematicsYork UniversityNorth YorkCanada
  2. 2.AT & T Bell LaboratoriesMurray Hill

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