A geometry-based relaxation algorithm for equilibrating a trivalent polygonal network in two dimensions and its implications
Kai Xu

TL;DR
This paper introduces a geometry-based relaxation algorithm for simulating the equilibration of trivalent polygonal networks in 2D, supporting the ellipse packing hypothesis and revealing patterns consistent with known growth laws.
Contribution
It presents a novel geometrical relaxation algorithm implemented in Python that models 2D network equilibration and supports the ellipse packing hypothesis.
Findings
The algorithm simulates the transition from inscribed polygons to maximal inscribed ellipses.
The Aboav-Weaire law holds statistically during relaxation.
Cell area and edge length patterns align with von-Neumann-Mullins law.
Abstract
The equilibration of a trivalent polygonal network in two dimensions (2D) is a universal phenomenon in nature, but the underlying mathematical mechanism remains unclear. In this study, a relaxation algorithm based on a simple geometrical rule was developed to simulate the equilibration. The proposed algorithm was implemented in Python language. The simulated relaxation changed the polygonal cell of the Voronoi network from an ellipse's inscribed polygon toward the ellipse's maximal inscribed polygon. Meanwhile, the Aboav-Weaire's law, which describes the neighboring relationship between cells, still holds statistically. The succeed of simulation strongly supports the ellipse packing hypothesis that was proposed to explain the dynamic behaviors of a trivalent 2D structure. The simulation results also showed that the edge of large cells tends to be shorter than edges of small cells, and…
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