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PATH INTEGRAL MONTE CARLO SIMULATIONS - STUDY OF THE EFFICIENCY OF ENERGY ESTIMATORS

机译:路径积分蒙特卡罗模拟-能源估算效率的研究

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This article presents a study of the relative efficiency of two commonly used energy estimators for path integral Monte Carlo (MC) simulations; the Barker estimator and the virial estimator. Two different path integral MC algorithms are considered; the simple algorithm augmented with whole chain moves and the normal-mode algorithm. The behavior of the two estimators is analyzed in some model systems and the suitability of its application is discussed, considering the general characteristics of the systems to be simulated. It is concluded that there is no obvious choice when it comes to decide which estimator to use. Instead, each one may be the most appropriate depending on the specific conditions of the simulation. Identical conclusions are drawn for both algorithms considered here. For low temperature systems or with high gradient potentials, where quantum effects are more significant, the Barker estimator is to be preferred as the variance of the mean energy is smaller. On the other hand, for high temperature systems or with low gradient potentials, where quantum effects are less significant, the virial estimator has a smaller variance of the mean energy. (C) 1995 American Institute of Physics. [References: 7]
机译:本文介绍了两种用于路径积分蒙特卡罗(MC)模拟的常用能量估算器的相对效率的研究。巴克估计器和维里尔估计器。考虑了两种不同的路径积分MC算法;简单的算法加上整条链运动和普通模式算法。考虑到要模拟的系统的一般特性,在某些模型系统中分析了两个估计器的行为,并讨论了其适用性。结论是,在决定使用哪个估计量时没有明显的选择。取而代之的是,根据模拟的特定条件,每个选项可能都是最合适的。对于这里考虑的两种算法得出了相同的结论。对于量子效应更为显着的低温系统或具有高梯度电势的系统,最好使用Barker估计器,因为平均能量的方差较小。另一方面,对于量子效应不太明显的高温系统或梯度电位较低的系统,病毒式估计器的平均能量方差较小。 (C)1995年美国物理研究所。 [参考:7]

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