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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. An interesting aspect of this is that such large flat parts are also found in large triangulations 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.
In order to efficiently handle a linear number of reducible configurations, we need them to have certain robustness that could also be useful in other applications. All our reducible configurations are what is known as D-reducible.



Why the gatekeeping of the nature of mathematical writing then? Writing about a 4 color system, yet across 96 pages, not a single page even uses 4 colors?
They actually did bother to make graphs, but not a single page even demonstrates 4 colors on any page simultaneously?
Come on, there should be better standards than that these days…
I’ve already explained to you why every professional discipline uses domain specific terminology. I get the impression this is the first time you’ve seen a scientific paper in your entire life. Why would they bother make a graph of 4 colors on a page, what the fuck would that even illustrate? The 4 color theorem itself isn’t what’s being discussed. It’s the algorithm that’s novel. You just have to accept the fact that this is serious research, and you’re not the target audience for it.
The algorithm can’t be discussed along with at least a few planar graphs in full color?
I never said anything against their studies, just their publication. They could have easily rounded that up to 100 pages with 4 extra pages in full color.
Can you explain how these planar graphs in full color help make the algorithm more clear? Please do elaborate on what additional explanatory power these would add.
If you study color, you don’t go at it colorblind.
Why are you defending the lack of full 4 color graphs, along with the 96 pages of text and math?
As I’ve already explained, and you promptly ignored, the paper isn’t about studying color. It’s about a specific mathematical algorithm that solves the theorem in linear time. The 96 page paper is about the algorithm. What part of that are you still struggling to comprehend?
I solve Rubik’s Cubes blindfolded behind my back. Yay for me right? No joke either.
Still, there’s no reason that mathematical experts can’t come up with an intuitive visual representation of their works.
I followed the works of Steven Wittens, aka Wacko…
https://acko.net/
He actually visualizes mathematics.
Because sometimes there is no intuitive visualization, or the visualization may even be deceptive. E.g. … the Coloring Problem is not literally about colors. It’s not even about maps. It’s about the abstraction itself. It’s about the math.
RGBXY
You got a 5 dimensional system right there.
Its not that hard, except for the people that don’t understand multiple dimensions…