Knotting probability [PK(N)] is defined by the probability of an N-noded random polygon being topologically equivalent to a given knot K. For several nontrivial knots we numerically evaluate the knotting probabilities for Gaussian and rod-bead models. We find that they are well approximated by the following formula: PK(N)=C(K)[\~N/N(K)]m(K)exp[-\~N/N(K)] where \~N=N-Nᵢₙᵢ(K), and that the fitting parameters C(K), N(K), and Nᵢₙᵢ(K) are model dependent, while m(K) is not. We suggest that given a knot K, the exponent m(K) should be universal: it is independent of models of random polygon and is determined only by the knot K.
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Deguchi et al. (1997) studied this question.
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