The Four Color Theorem with Linearly Many Reducible Configurations and Near-Linear Time Coloring

TL;DR

This paper presents a near-linear time algorithm for 4-coloring planar graphs, leveraging a new structural insight that finds many reducible configurations, improving the previous quadratic time approach.

Contribution

It generalizes the Four Color Theorem by showing the existence of linearly many reducible configurations, enabling a more efficient coloring algorithm.

Findings

Achieves 4-coloring in O(n log n) time, improving over previous quadratic algorithms.

Shows that planar triangulations contain linearly many reducible configurations or cycles.

Extends the structural understanding of planar graphs, potentially applicable to higher surfaces.

Abstract

We give a near-linear time 4-coloring algorithm for planar graphs, improving on the previous quadratic time algorithm by Robertson et al. from 1996. Such an algorithm cannot be achieved by the known proofs of the Four Color Theorem (4CT). Technically speaking, we show the following significant generalization of the 4CT: every planar triangulation contains linearly many pairwise non-touching reducible configurations or pairwise non-crossing obstructing cycles of length at most 5 (which all allow for making effective 4-coloring reductions). The known proofs of the 4CT only show the existence of a single reducible configuration or obstructing cycle in the above statement. The existence is proved using the discharging method based on combinatorial curvature. It identifies reducible configurations in parts where the local neighborhood has positive combinatorial curvature. Our result significantly strengthens the known proofs of 4CT, showing that we can also find reductions in large ``flat" parts where the curvature is zero, and moreover, we can make reductions almost anywhere in a given planar graph. This also opens possibilities for extensions to higher surfaces since we can find such flat parts in any large-width triangulation of any fixed surface. From a computational perspective, the old proofs allowed us to apply induction on a problem that is smaller by some additive constant. The inductive step took linear time, resulting in a quadratic total time. With our linear number of reducible configurations or obstructing cycles, we can reduce the problem size by a constant factor. Our inductive step takes $O(n\log n)$ time, yielding a 4-coloring in $O(n\log n)$ total time. To efficiently handle a linear number of reducible configurations, we need them to be sufficiently robust to be useful in other applications. All our reducible configurations are what is known as D-reducible.