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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.



Is this…
Is this the theorem that it only takes 4 different colors to differentiate boundaries between states/countries on a map?
Geez, why are these sort of articles so complicated to read?
Feels AI generated…
Yes, but the theorem you mention is about much more than just about colors. The whole thing about colors on a map is just one accessible illustration of a very deep and general property of graphs. It has many more applications.
Geez, why do people feel the need to leave vapid comments like this. Just because you have trouble understanding something doesn’t make it AI generated lmfao.
I have no problem reading it at all. I speak on behalf of all the people out there that would indeed have trouble reading it, as they didn’t even reference the simple concept of a map, where such studies originated in the first place.
They exclusively use complicated terms like ‘planar graph’, which makes sense to me, but I read no simplified comparison to a simple map.
I’m also familiar with topology, and know that if a map was to be made on a torus (donut in laymans terms), that it would take 6 colors to guarantee distinguishing one region from another.
Sometimes simple minded people like to learn as well, so why no reference to a simple map?
Because it’s a research paper, not a textbook on graph theory.
A planar graph is (loosely) a graph that can be drawn on a single sheet of paper without intersecting the branches. Not very complicated. More importantly, you can find these definitions in any graph theory textbook.
If you would like to read a textbook on graph theory, I highly recommend A First Course on Graph Theory by Gary Chartrand and Ping Zhang. It’s a Dover book (cheap), and it’s available on LibGen. You will notice that their textbook is printed in black and white, yet their explanation of the Coloring Problem is quite crisp regardless.
Because people who have no background in graph theory are simply not the audience for this paper.
Wait, you can find textbooks these days that haven’t been burned in favor of digital subscriptions?
Unironically yes.
So when I did my undergraduate math courses…yeah, those books and assignments were locked behind digital subscriptions, so I cannot access them anymore. I think the reason is that these systems do automatic grading of homework, so they don’t have to hire as many graders. And then for the books, they probably (correctly) assume they’re on LibGen or at the library. where they won’t need to use the ma
But advanced undergraduate and graduate level books can usually be bought like ordinary books…or borrowed from a shadow library (make sure you’re running uBlock Origin).
In fact, some authors even give out their books for free, and most authors are willing to send you an electronic copy if you ask. Authors make exactly $0 per sale.
Removed by mod
Nah you Dunning-Kruger ass buffoon, I was trying to be helpful, in particular to show people who don’t know shit about graph theory that it is no longer inaccessible knowledge. You clearly need to reread whatever graph theory book you have if you seriously think that planar graphs need to be explained in a research paper or that the Coloring Problem needs to be illustrated with literal colors.
Also, you said you’re familiar with topology. Topology and graph theory are related but distinct subjects! In topological graph theory, the topology is an additional structure imposed upon a graph. So knowledge about topology is mostly irrelevant for graph theory, except for topological graph theory results.
Render me a torus, I did that at age 17.
I can simplify my algorithm to less than 2 pages of text, without having to get ridiculous complicated about it.
Also the fuck you mean AI slop? The book I recommended (Chartrand and Zhang) predates AI.
Ok. And I’m still trying to convince people to stop taping magnets on the back of their phones, but they treat me like shit, as if I don’t know what a fucking compass sensor is…
You’re speaking on behalf of fictional people that you made up. They used the terms that are typically used in these types of papers. The reason papers use precise terminology is because people working in the field agreed on a common set of terms. This paper isn’t written for layman consumption, but to share research with other experts. Perhaps you’re not used to reading actual papers, and confuse the formal and precise language with what you’re used to seeing in popular mechanics summaries?
OK
Out of all 96 pages, I only see monochrome wireframe graphs. Okay sure a couple pages used some light blue lines, but holy fuck, out of 96 pages regarding the 4 color theorem and not a single page even has 4 colors?
Like fucking hell, all that effort to write a lengthy paper on 4 colors yet can’t even be bothered to make a proper visual representation?
Seems closer to trying to teach painting to a color blind person 🤦♂️
They literally invented a whole new linear algorithm when the best possible approach before was quadratic. And here’s you claiming that it doesn’t warrant 96 pages. Incredible stuff. Maybe just stick to coloring with crayons instead of attempting to discuss serious papers. Just a thought.
If your entire paper is focused on color study, and you have the technology at your disposal to render over 16 million colors, then is it too much to ask to have an actual visual color representation of what the paper is about? 4 colors, that’s all.
Jebus H Christ, is this an April Fool’s post or something?
Fuck, I study and program photochromatography, at least I have example works to show in full color.
I get a distinct impression that you don’t even understand the significance of the paper. The entire paper is focused on the novel algorithm they came up with which turns O(n^2) operation into O(nlogn). That’s a huge finding. If you have no appreciation for math, what are you even doing trolling around this community?
I’m not even trolling, I’m saying there are much better ways to represent mathematical algorithms than Greek letters and monochrome graphics, especially when the subject matter involves multiple colors.
I am no troll, I learned the basics of Calculus and Trigonometry at age 10, and went on to pursue 3D graphics and photochromatography by age 17.
I’m 43 now for reference. I’m also not dismissing their works at all, I’m just disappointed that they couldn’t be bothered to add another 4 pages of actual full color graphs to literally show what they’re talking about.