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arXiv 1312.0907cond-mat.soft
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颗粒熵的数值计算

Numerical calculation of granular entropy

Daniel Asenjo, Fabien Paillusson, Daan Frenkel

摘要:

我们提出的数值模拟,使我们能够计算的方式,其中$N$颗粒可以包装成一个给定的体积$V$的数量。我们的技术修改了Xu等人的方法。106,245502(2011)),并且比现有的直接枚举方法性能好200多个数量级。我们用我们的方法来研究系统的大小依赖的不同包装的系统多达128个多分散软盘的数量。我们表明,即使颗粒是可区分的,我们必须包括一个因素$1/N!$,以确保熵不改变时,在相同的宏观状态下的系统之间交换粒子。我们的模拟提供了强有力的证据表明,包装熵,适当定义时,是广泛的。由于不同的填充是以不相等的概率创建的,因此自然将填充熵表示为$S=-\sum_i p_i\ln p_i -\ln N!$,其中$p_i$表示生成第$i$个填充的概率。我们可以可靠地计算这个量,它也是广泛的。因此,颗粒熵(重新)定义,而不同于爱德华兹提出的假设(J. Phys.:Condens.Matter 2,SA 63(1990))确实具有Edwards假定的所有性质。

英文摘要:

We present numerical simulations that allow us to compute the number of ways in which $N$ particles can pack into a given volume $V$. Our technique modifies the method of Xu et al. (Phys. Rev. Lett. 106, 245502 (2011)) and outperforms existing direct enumeration methods by more than 200 orders of magnitude. We use our approach to study the system size dependence of the number of distinct packings of a system of up to 128 poly-disperse soft disks. We show that, even though granular particles are distinguishable, we have to include a factor $1/N!$ to ensure that the entropy does not change when exchanging particles between systems in the same macroscopic state. Our simulations provide strong evidence that the packing entropy, when properly defined, is extensive. As different packings are created with unequal probabilities, it is natural to express the packing entropy as $S=-\sum_i p_i\ln p_i -\ln N!$, where $p_i$ denotes the probability to generate the $i$-th packing. We can compute this quantity reliably and it is also extensive. The granular entropy thus (re)defined, whilst distinct from the one proposed by Edwards assumed (J. Phys.: Condens.Matter 2, SA63(1990)), does have all the properties Edwards assumed.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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