English

Pair correlation function based on Voronoi topology

Disordered Systems and Neural Networks 2023-12-14 v2

Abstract

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.

Keywords

Cite

@article{arxiv.2210.09731,
  title  = {Pair correlation function based on Voronoi topology},
  author = {Vasco M. Worlitzer and Gil Ariel and Emanuel A. Lazar},
  journal= {arXiv preprint arXiv:2210.09731},
  year   = {2023}
}

Comments

8 pages, 9 figures

R2 v1 2026-06-28T03:54:08.161Z