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Quadratic Complexity of Voronoi Diagrams in R3\mathbb{R}^3 for Lines in a Single Ruling of a Regulus

Eunku Park

Source record

Source: arXiv

Published: Aug 27, 2026

arXiv: 2608.27114

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Source abstract

We study nearest and farthest Voronoi diagrams of lines in R3\mathbb{R}^3 under the Euclidean metric when all nn lines belong to one ruling of a smooth doubly ruled real quadric. For arbitrary line sites, the combinatorial complexity of the nearest Voronoi diagram is known only to lie between Ω(n2)Ω(n^2) and O(n3+ε)O(n^{3+\varepsilon}). Under general-position assumptions, we prove that both diagrams in the ruling class have at most 4n(n−3)4n(n-3) vertices and O(n2)O(n^2) total combinatorial complexity. Conversely, for every n≥4n \ge 4, one ruling of a fixed non-rotational one-sheeted hyperboloid contains a general-position set of nn lines with at least (n−2)(n−3)/2(n-2)(n-3)/2 distinct regular nearest vertices, where regular means that exactly four lines support the vertex and their three defining bisectors meet transversely. Thus the worst-case complexity of the nearest Voronoi diagram in this class is Θ(n2)Θ(n^2), while the farthest diagram has Θ(n2)Θ(n^2) complexity for every general-position input, since it has exactly n(n−1)n(n-1) three-dimensional cells. Under the Plücker embedding, the ruling is a conic, and the condition for a line to be tangent to a Euclidean sphere restricts to a binary quartic. At a regular vertex, the four supporting parameters exhaust its roots, and sign alternation forces two arcs of the parameter circle to be site-free. This leaves only n(n−3)/2n(n-3)/2 possible cyclic support types, while Bézout's theorem bounds the number of centers for each type by eight. The same reduction yields an exact O(n2)O(n^2)-time algorithm that, after cyclically sorting the site parameters, enumerates all finite nearest and farthest vertices as constant-degree real univariate representations.

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Quadratic Complexity of Voronoi Diagrams in $\mathbb{R}^3$ for Lines in a Single Ruling of a Regulus — Mathematical Frontier Network