Scholay

学术搜索 · AI 审稿 · LaTeX 协作

Structural properties of hyperuniform Voronoi networks

作者:Eli Newby, Wenlong Shi, Yang Jiao, Réka Albert, Salvatore Torquato · 发表于:Physical review. E · 年份:2025 · DOI:10.1103/physreve.111.034123 · 被引用次数:6 · 研究领域:Complex Network Analysis Techniques、Data Visualization and Analytics、Theoretical and Computational Physics

Disordered hyperuniform many-particle systems are recently discovered exotic states of matter, characterized by the complete suppression of normalized infinite-wavelength density fluctuations, as in perfect crystals, while lacking conventional long-range order, as in liquids and glasses. In this work, we begin a program to quantify the structural properties of nonhyperuniform and hyperuniform networks. In particular, large two-dimensional (2D) Voronoi networks (graphs) containing approximately 10,000 nodes are created from a variety of different point configurations, including the antihyperuniform hyperplane intersection process (HIP), nonhyperuniform Poisson process, nonhyperuniform random sequential addition (RSA) saturated packing, and both non-stealthy and stealthy hyperuniform point processes. We carry out an extensive study of the Voronoi-cell area distribution of each of the networks by determining multiple metrics that characterize the distribution, including their average areas and corresponding variances as well as higher-order cumulants (i.e., skewness γ_{1} and excess kurtosis γ_{2}). We show that the HIP distribution is far from Gaussian, as evidenced by a high skewness (γ_{1}=3.16) and large positive excess kurtosis (γ_{2}=16.2). The Poisson (with γ_{1}=1.07 and γ_{2}=1.79) and non-stealthy hyperuniform (with γ_{1}=0.257 and γ_{2}=0.0217) distributions are Gaussian-like distributions, since they exhibit a small but positive skewness and excess kurtosis. The RSA ...