Monte Carlo Procedures for Generation of Nonintersecting Chains

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Abstract
A new method is described for high‐speed computer generation of non‐self‐intersecting random walks for use as models of coiling‐type polymer molecules. Previous methods for the unbiased generation of self‐avoiding random walks have proved to be statistically inadequate when certain intramolecular interactions are assumed to exist. This situation arises because energetically important configurations may have a very low probability of occurrence in a normal sample. With this problem in mind, a method of generating samples in a biased fashion has been developed. The procedure allows energetically important configurations to be generated in such a way that the actual amount of bias can be calculated and compensated for, and the samples so obtained can be incorporated with those obtained in a normal, unbiased way. Data are presented to show how the attrition attending the generation of samples depends on bias.