欧几里得晶格上聚合物链模型的蒙特卡罗模拟

I. Živić, D. Marčetić, Sunčica Elezović Hadžić
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引用次数: 0

摘要

我们研究了柔性聚合物在良好溶剂和均质环境下的关键特性,通过自我避免随机行走来模拟。采用PERM蒙特卡罗模拟方法,生成了最大长度为N=2000步的正方形和简单立方晶格上的聚合物链。我们大致列举了长度为N的不同聚合物链构型的数目,并分析了其由连通性常数μ和熵临界指数γ决定的渐近行为(对于大N)。此外,我们研究了有效临界指数集휈푁的行为,控制长度为N的聚合物链的端到端距离。我们已经确定,在二维휈푁中,随着N单调增加,而在三维中,当N增加时,它单调减少。得到的两个空间维度的值휈푁在超长链的范围内进行了外推。最后,我们讨论了我们的结果,并将其与欧几里得晶格上聚合物的结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MONTE CARLO SIMULATIONS OF A POLYMER CHAIN MODEL ON EUCLIDEAN LATTICES
We studied the critical properties of flexible polymers, modelled by self-avoiding random walks, in good solvents and homogeneous environments. By applying the PERM Monte Carlo simulation method, we generated the polymer chains on the square and the simplecubic lattice of the maximal length of N=2000 steps.We enumerated approximately the number of different polymer chain configurations of length N,and analysed its asymptotic behaviour (for large N), determined by the connectivity constant μ and the entropic critical exponent γ. Also, we studied the behaviour of the set of effective critical exponents 휈푁, governing the end-to-end distance of a polymer chain of length N. We have established that in two dimensions 휈푁monotonically increases with N, whereas in three dimensions itmonotonically decreases when Nincreases. Values of 휈푁, obtained for both spatial dimensions have been extrapolated in the range of very long chains.In the end, we discuss and compare our results to those obtained previously for polymers on Euclidean lattices.
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