Papers for

computational geometry engineers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Improved vertex coloring method reduces imbalance in triangle networks

Polychromatic 2-colorings with Bounded Discrepancy for Triangulations

Abstract: A polychromatic $2$-coloring of a triangulation is a $2$-coloring of the vertices such that no face is monochromatic. The discrepancy of a coloring is the maximum difference between the sizes of the color classes. Asayama and Matsumoto (Graphs and Combinatorics, 2022) proved that every triangulation admits a polychromatic $2$-coloring with discrepancy at most $\tfrac{5n-16}{9}$, and that there exists a class of triangulations for which every polychromatic $2$-coloring has discrepancy at least $\tfrac{n}{3} - 2$, where $n$ is the number of vertices. We improve the upper bound, showing that every triangulation admits a polychromatic $2$-coloring with discrepancy at most $\tfrac{3n-16}{7}$ and such a $2$-coloring can be computed in quadratic time. We also show a discrepancy of at most $n-\tfrac{4M}{3}$ for triangulations with a matching of size $M$. This implies, for example, that Delaunay triangulations admit a discrepancy of at most $\tfrac{n}{3}$. We provide a linear-time algorithm to compute a $2$-coloring whose discrepancy is at most $\tfrac{5n-24}{7}$. One of our results shows that any proper four coloring with the largest color class of size $\frac{n}{2}$ would imply a $2$-coloring with discrepancy at most $\frac{n}{3}$. The existence of such a proper coloring has been recently confirmed by Kawarabayashi, Yoneda, and Yoneda (arXiv 2026). Therefore the two results together confirm the discrepancy of at most $\frac{n}{3}$ for triangulations.

Fri 25 SeptComputational Geometry
The gist
The paper studies a way to color the points (vertices) of a triangle-filled network so that no triangle has all points the same color, using just two colors. The goal is to keep the number of points in each color group balanced, minimizing how uneven the groups are. The authors improved previous results by showing how to achieve a better balance between the two colors and provided efficient algorithms to find these colorings. They also connected their work to special types of triangle networks called Delaunay triangulations and linked their findings to recent results on four-colorings of these graphs.
Open → 2609.31574v1

Linear method clarifies tetrahedron edge bisection choices

Multiform Longest Edge Bisection of Tetrahedra via Sextuple Permutations

Abstract: We introduce a new formulation of the Longest Edge Bisection (LEB) of tetrahedra entirely in sextuple space R6, where tetrahedra are represented by the squares of their edge lengths. This representation renders the LEB refinement equations fully linear and eliminates the need for coordinate-based data structures. A central difficulty in three-dimensional LEB arises when a tetrahedron possesses multiple longest edges, making the refinement rule intrinsically multivalued. We formalize this phenomenon through the notion of Multiform Longest Edge Bisection (MLEB), which systematically explores all admissible longest-edge choices. To encode this multivalued behavior, we introduce the concept of bisection patterns, defined as sequences of sextuple permutations governing the refinement process. We prove that the set of sextuples sharing a common LEB pattern forms a convex region in R6. For structurally significant families of tetrahedra, including the R1+ family and the Liu-Joe family, we show that the infinite refinement tree collapses into a finite directed graph with eight states. Remarkably, both families are governed by the same graph, differing only in their initial state. This directed-graph formulation provides a unified combinatorial description of the refinement process and offers an efficient computational framework for deep iterative LEB analysis.

Tue 22 SeptComputational Geometry
The gist
The paper tackles the problem of splitting a 3D shape called a tetrahedron along its longest edge, which becomes tricky when multiple longest edges exist. The authors represent these shapes using numbers that describe their edge lengths squared, making the math simpler and avoiding messy coordinate data. They introduce a way to handle all possible longest-edge choices systematically through sequences called bisection patterns. Their work shows these patterns form neat geometric regions and that complex refinement steps can be reduced to a small set of states, making analysis and computation easier.
Open → 2609.26522v1