Efficiency of the Incomplete Enumeration Algorithm for Monte-Carlo Simulation of Linear and Branched Polymers
Author:
Publisher
Springer Science and Business Media LLC
Subject
Mathematical Physics,Statistical and Nonlinear Physics
Link
http://link.springer.com/content/pdf/10.1007/s10955-005-5462-2.pdf
Reference30 articles.
1. A. D. Sokal, Monte-Carlo Methods for the Self Avoiding Walk 1995, in Monte Carlo and Molecular Dynamics Simulations in Polymer Science, K. Binder, ed. Oxford University Press New York 47–124, hep-lat/9405016.
2. Macromolecular dimensions obtained by an efficient Monte Carlo method without sample attrition
3. The pivot algorithm: A highly efficient Monte Carlo method for the self-avoiding walk
4. Nonlocal Monte Carlo algorithm for self-avoiding walks with fixed endpoints
Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Improving convergence of generalised Rosenbluth sampling for branched polymer models by uniform sampling;Journal of Physics A: Mathematical and Theoretical;2024-04-18
2. Correction: Efficiency of the Incomplete Enumeration Algorithm for Monte-Carlo Simulation of Linear and Branched Polymers;Journal of Statistical Physics;2023-11-06
3. Calculation of the connective constant for self-avoiding walks via the pivot algorithm;Journal of Physics A: Mathematical and Theoretical;2013-05-24
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