Abstract
A number of researchers have applied Monte Carlo techniques to questions of random knotting. (Chen, 1981; Deguchi and Tsurusaki, 1994; Frank-Kamenetskii, et.al., 1975; Jense van Rensburg and Whittington, 1990 and 1991a;Koniaris and Muthukumar, 1991; Mansfield, 1994; Michels and Wiegel, 1986;ten Brinke and Hadziioannou, 1987 ; Vologodskii, et.al., 1974 and 1975.) These studies seek to understand the knotting statistics of randomly grown knots. Their relevance to the physical sciences is primarily in the field of polymer or biopolymer configurations. These computations typically require generation of random knots followed by characterization of the knot state of each generated configuration. So obviously, knot recognition algorithms are essential to such computations.KeywordsHamilton CycleRecognition AlgorithmCongruence ClassJones PolynomialAlexander PolynomialThese 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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