On monte carlo and molecular dynamics methods inspired by Tsallis statistics: Methodology, optimization, and application to atomic clusters
On monte carlo and molecular dynamics methods inspired by Tsallis statistics: Methodology, optimization, and application to atomic clusters
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DOI：
10.1063/1.475203
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发表时间：
1997-12-01
影响因子：
4.4
通讯作者：
Straub, JE
中科院分区：
文献类型：
--
作者：
Andricioaei, I;Straub, JE
介绍了在平衡态热力学性质计算中提供相空间增强采样的广义蒙特卡罗和分子动力学算法。该算法的样本试验移动来自广义统计分布的吉布斯-香农熵Tsallis提出的修改。一维模型势的计算结果表明，该算法大大提高了平衡平均值的计算速度和收敛速度。比较与标准的大都会蒙特卡罗和J-步行算法的Franz，Freeman和娃娃。13个原子的Lennard-Jones团簇的应用表明，该算法可以很容易地应用到复杂的分子系统。(C)1997年美国物理学会。
Generalized Monte Carlo and molecular dynamics algorithms which provide enhanced sampling of the phase space in the calculation of equilibrium thermodynamic properties is presented. The algorithm samples trial moves from a generalized statistical distribution derived from a modification of the Gibbs-Shannon entropy proposed by Tsallis. Results for a one-dimensional model potential demonstrate that the algorithm leads to a greatly enhanced rate of barrier crossing and convergence in the calculation of equilibrium averages. Comparison is made with standard Metropolis Monte Carlo and the J-walking algorithm of Franz, Freeman and Doll. Application to a 13-atom Lennard-Jones cluster demonstrates the ease with which the algorithm may be applied to complex molecular systems. (C) 1997 American Institute of Physics.