论文标题
基于Voronoi拓扑的配对相关函数
Pair correlation function based on Voronoi topology
论文作者
论文摘要
该对相关函数（PCF）已证明是一种有效的工具，可以通过简单性以及对模拟和实验数据的适用性进行分析。但是，作为平均数量，即使这些差异可能对系统属性产生重大影响，PCF也无法捕获粒子排列的细微结构差异。在这里，我们使用voronoi拓扑来引入PCF的离散版本，该版本突出显示局部粒子间拓扑配置。在几个示例中证明了Voronoi PCF的优势，包括结晶，超一样系统和活性系统，显示了聚类和巨型数量波动。
The pair correlation function (PCF) has proven an effective tool for analyzing many physical systems due to its simplicity and its applicability to simulated and experimental data. However, as an averaged quantity, the PCF can fail to capture subtle structural differences in particle arrangements, even when those differences can have a major impact on system properties. Here, we use Voronoi topology to introduce a discrete version of the PCF that highlights local inter-particle topological configurations. The advantages of the Voronoi PCF are demonstrated in several examples including crystalline, hyperuniform, and active systems showing clustering and giant number fluctuations.
