An infinite swapping approach to the rare-event sampling problem
An infinite swapping approach to the rare-event sampling problem
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DOI：
10.1063/1.3643325
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发表时间：
2011-10-07
影响因子：
4.4
通讯作者：
Gubernatis, J. E.
中科院分区：
文献类型：
--
作者：
Plattner, Nuria;Doll, J. D.;Gubernatis, J. E.
我们描述了一种新的方法来稀有事件的蒙特卡罗抽样问题。该技术利用对称化策略来创建更高度连接的概率分布，因此比其原始的潜在稀疏对应物更容易采样。在讨论了该方法的正式轮廓和设计技术的实际实施，我们说明了该技术的实用性与一系列的数值应用程序不同的复杂性和稀有事件字符的Lennard-Jones集群。(C)2011年美国物理学会。[doi：10.1063/1.3643325]
We describe a new approach to the rare-event Monte Carlo sampling problem. This technique utilizes a symmetrization strategy to create probability distributions that are more highly connected and, thus, more easily sampled than their original, potentially sparse counterparts. After discussing the formal outline of the approach and devising techniques for its practical implementation, we illustrate the utility of the technique with a series of numerical applications to Lennard-Jones clusters of varying complexity and rare-event character. (C) 2011 American Institute of Physics. [doi:10.1063/1.3643325]