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通过条件熵量化无序:在流体混合中的应用。

Quantifying disorder through conditional entropy: an application to fluid mixing.

机构信息

SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, Scotland, United Kingdom.

出版信息

PLoS One. 2013 Jun 10;8(6):e65617. doi: 10.1371/journal.pone.0065617. Print 2013.

Abstract

In this paper, we present a method to quantify the extent of disorder in a system by using conditional entropies. Our approach is especially useful when other global, or mean field, measures of disorder fail. The method is equally suited for both continuum and lattice models, and it can be made rigorous for the latter. We apply it to mixing and demixing in multicomponent fluid membranes, and show that it has advantages over previous measures based on Shannon entropies, such as a much diminished dependence on binning and the ability to capture local correlations. Further potential applications are very diverse, and could include the study of local and global order in fluid mixtures, liquid crystals, magnetic materials, and particularly biomolecular systems.

摘要

在本文中,我们提出了一种通过使用条件熵来量化系统无序程度的方法。当其他全局或平均场无序度量方法失效时,我们的方法特别有用。该方法同样适用于连续体和晶格模型,并且可以为后者提供严格的方法。我们将其应用于多组分流体膜中的混合和离析,并表明它优于基于香农熵的先前度量方法,例如对分箱的依赖性大大降低,并且能够捕获局部相关性。进一步的潜在应用非常多样化,可能包括研究流体混合物、液晶、磁性材料以及特别是生物分子系统中的局部和全局有序性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8f8/3677935/a0403db2b0b3/pone.0065617.g001.jpg

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