Entropy estimates of a hard sphere system by data compression of Monte Carlo simulation data,Soft Matter

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Entropy estimates of a hard sphere system by data compression of Monte Carlo simulation data
Soft Matter ( IF 2.9 ) Pub Date : 2020-03-11 , DOI: 10.1039/c9sm01616c
E. F. Walraven _{1,

2,

3,

4} , F. A. M. Leermakers _{1,

2,

3,

4}

Affiliation

Data compression algorithms remove redundant information from a file. The extent to which a file size is reduced is a measure of the entropy. Recently, it has been suggested to use this technique to find the entropy from a simulation of a physical system. Here, we apply this technique to estimate the entropy from Monte Carlo simulations of the hard sphere system. Numerical results compare well with the limited available entropy estimates from the laborious thermodynamic integration method, while this new algorithm is much faster. Our results show the phase transition by calculation of the entropy for a large number of densities. A common tangent method is used to find the coexistence densities for the fluid–solid phase transition. The upper density deviates from the established density from the literature, while the lower density compares very well.

中文翻译：

蒙特卡罗模拟数据的数据压缩对硬球系统的熵估计

数据压缩算法从文件中删除冗余信息。文件大小的减小程度是熵的度量。近来，已经建议使用该技术从物理系统的仿真中找到熵。在这里，我们应用这种技术从硬球系统的蒙特卡洛模拟中估计熵。数值结果与费力的热力学积分方法提供的有限的可用熵估计值相比较，而这种新算法的速度要快得多。我们的结果通过计算大量密度的熵显示出相变。常用的切线方法用于找到流固相变的共存密度。上限密度与文献中确定的密度不同，

更新日期：2020-04-24

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