Five color theorem

Last updated
A Five-Color Map 4CT Non-Counterexample 1.svg
A Five-Color Map

The five color theorem is a result from graph theory that given a plane separated into regions, such as a political map of the countries of the world, the regions may be colored using no more than five colors in such a way that no two adjacent regions receive the same color.

Contents

The five color theorem is implied by the stronger four color theorem, but is considerably easier to prove. It was based on a failed attempt at the four color proof by Alfred Kempe in 1879. Percy John Heawood found an error 11 years later, and proved the five color theorem based on Kempe's work.

Outline of the proof by contradiction

First of all, one associates a simple planar graph to the given map, namely one puts a vertex in each region of the map, then connects two vertices with an edge if and only if the corresponding regions share a common border. The problem is then translated into a graph coloring problem: one has to paint the vertices of the graph so that no edge has endpoints of the same color.

Because is a simple planar, i.e. it may be embedded in the plane without intersecting edges, and it does not have two vertices sharing more than one edge, and it does not have loops, then it can be shown (using the Euler characteristic of the plane) that it must have a vertex shared by at most five edges. (Note: This is the only place where the five-color condition is used in the proof. If this technique is used to prove the four-color theorem, it will fail on this step. In fact, an icosahedral graph is 5-regular and planar, and thus does not have a vertex shared by at most four edges.) Find such a vertex, and call it .

Now remove from . The graph obtained this way has one fewer vertex than , so we can assume by induction that it can be colored with only five colors. If the coloring did not use all five colors on the five neighboring vertices of , it can be colored in with a color not used by the neighbors. So now look at those five vertices , , , , that were adjacent to in cyclic order (which depends on how we write G). So we can assume that , , , , are colored with colors 1, 2, 3, 4, 5 respectively.

Now consider the subgraph of consisting of the vertices that are colored with colors 1 and 3 only and the edges connecting them. To be clear, each edge connects a color 1 vertex to a color 3 vertex (this is called a Kempe chain). If and lie in different connected components of , we can swap the 1 and 3 colors on the component containing without affecting the coloring of the rest of . This frees color 1 for completing the task. If on the contrary and lie in the same connected component of , we can find a path in joining them that consists of only color 1 and 3 vertices.

Now turn to the subgraph of consisting of the vertices that are colored with colors 2 and 4 only and the edges connecting them, and apply the same arguments as before. Then either we are able to reverse the 2-4 coloration on the subgraph of containing and paint color 2, or we can connect and with a path that consists of only color 2 and 4 vertices. Such a path would intersect the 1-3 colored path we constructed before since through were in cyclic order. This is clearly absurd as it contradicts the planarity of the graph.

So can in fact be five-colored, contrary to the initial presumption.

Linear time five-coloring algorithm

Multiple authors, beginning with Lipton and Miller in 1978, have studied efficient algorithms for five-coloring planar graphs. The algorithm of Lipton and Miller took time , [1] but subsequent researchers reduced the time bound to . [2] [3] [4] [5] [6] The version below is from a 1996 paper by Robertson, Sanders, Seymour, and Thomas, which describes it briefly in connection with a slower -time algorithm for four-coloring. [7] The algorithm as described here operates on multigraphs and relies on the ability to have multiple copies of edges between a single pair of vertices. It is based on Wernicke's theorem, which states the following:

Wernicke's theorem: Assume G is planar, nonempty, has no faces bounded by two edges, and has minimum degree 5. Then G has a vertex of degree 5 which is adjacent to a vertex of degree at most 6.

We will use a representation of the graph in which each vertex maintains a circular linked list of adjacent vertices, in clockwise planar order.

In concept, the algorithm is recursive, reducing the graph to a smaller graph with one less vertex, five-coloring that graph, and then using that coloring to determine a coloring for the larger graph in constant time. In practice, rather than maintain an explicit graph representation for each reduced graph, we will remove vertices from the graph as we go, adding them to a stack, then color them as we pop them back off the stack at the end. We will maintain three stacks:

The algorithm works as follows:

  1. In the first step, we collapse all multiple edges to single edges, so that the graph is simple. Next, we iterate over the vertices of the graph, pushing any vertex matching the conditions for S4 or S5 onto the appropriate stack.
  2. Next, as long as S4 is non-empty, we pop v from S4 and delete v from the graph, pushing it onto Sd, along with a list of its neighbors at this point in time. We check each former neighbor of v, pushing it onto S4 or S5 if it now meets the necessary conditions.
  3. When S4 becomes empty, we know that our graph has minimum degree five. If the graph is empty, we go to the final step 5 below. Otherwise, Wernicke's Theorem tells us that S5 is nonempty. Pop v off S5, delete it from the graph, and let v1, v2, v3, v4, v5 be the former neighbors of v in clockwise planar order, where v1 is the neighbor of degree at most 6. We check if v1 is adjacent to v3 (which we can do in constant time due to the degree of v1). There are two cases:
    1. If v1 is not adjacent to v3, we can merge these two vertices into a single vertex. To do this, we remove v from both circular adjacency lists, and then splice the two lists together into one list at the point where v was formerly found. Provided that v maintains a reference to its position in each list, this can be done in constant time. It's possible that this might create faces bounded by two edges at the two points where the lists are spliced together; we delete one edge from any such faces. After doing this, we push v3 onto Sd, along with a note that v1 is the vertex that it was merged with. Any vertices affected by the merge are added or removed from the stacks as appropriate.
    2. Otherwise, v2 lies inside the face outlined by v, v1, and v3. Consequently, v2 cannot be adjacent to v4, which lies outside this face. We merge v2 and v4 in the same manner as v1 and v3 above.
  4. Go to step 2.
  5. At this point S4, S5, and the graph are empty. We pop vertices off Sd. If the vertex were merged with another vertex in step 3, the vertex that it was merged with will already have been colored, and we assign it the same color. This is valid because we only merged vertices that were not adjacent in the original graph. If we had removed it in step 2 because it had at most 4 adjacent vertices, all of its neighbors at the time of its removal will have already been colored, and we can simply assign it a color that none of its neighbors is using.

Alternate proof

Kainen (1974) provides a simplified proof of the five color theorem, based on the non-planarity of K6 (the complete graph with 6 vertices) and graph minors. This proof generalizes to graphs that can be made planar by deleting 2 edges. [8]

See also

Related Research Articles

<span class="mw-page-title-main">Four color theorem</span> Statement in mathematics

In mathematics, the four color theorem, or the four color map theorem, states that no more than four colors are required to color the regions of any map so that no two adjacent regions have the same color. Adjacent means that two regions share a common boundary of non-zero length. It was the first major theorem to be proved using a computer. Initially, this proof was not accepted by all mathematicians because the computer-assisted proof was infeasible for a human to check by hand. The proof has gained wide acceptance since then, although some doubts remain.

<span class="mw-page-title-main">Graph theory</span> Area of discrete mathematics

In mathematics, graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects. A graph in this context is made up of vertices which are connected by edges. A distinction is made between undirected graphs, where edges link two vertices symmetrically, and directed graphs, where edges link two vertices asymmetrically. Graphs are one of the principal objects of study in discrete mathematics.

In graph theory, a planar graph is a graph that can be embedded in the plane, i.e., it can be drawn on the plane in such a way that its edges intersect only at their endpoints. In other words, it can be drawn in such a way that no edges cross each other. Such a drawing is called a plane graph or planar embedding of the graph. A plane graph can be defined as a planar graph with a mapping from every node to a point on a plane, and from every edge to a plane curve on that plane, such that the extreme points of each curve are the points mapped from its end nodes, and all curves are disjoint except on their extreme points.

<span class="mw-page-title-main">Bipartite graph</span> Graph divided into two independent sets

In the mathematical field of graph theory, a bipartite graph is a graph whose vertices can be divided into two disjoint and independent sets and , that is, every edge connects a vertex in to one in . Vertex sets and are usually called the parts of the graph. Equivalently, a bipartite graph is a graph that does not contain any odd-length cycles.

This is a glossary of graph theory. Graph theory is the study of graphs, systems of nodes or vertices connected in pairs by lines or edges.

<span class="mw-page-title-main">Graph coloring</span> Methodic assignment of colors to elements of a graph

In graph theory, graph coloring is a special case of graph labeling; it is an assignment of labels traditionally called "colors" to elements of a graph subject to certain constraints. In its simplest form, it is a way of coloring the vertices of a graph such that no two adjacent vertices are of the same color; this is called a vertex coloring. Similarly, an edge coloring assigns a color to each edge so that no two adjacent edges are of the same color, and a face coloring of a planar graph assigns a color to each face or region so that no two faces that share a boundary have the same color.

<span class="mw-page-title-main">Edge coloring</span> Problem of coloring a graphs edges such that meeting edges do not match

In graph theory, a proper edge coloring of a graph is an assignment of "colors" to the edges of the graph so that no two incident edges have the same color. For example, the figure to the right shows an edge coloring of a graph by the colors red, blue, and green. Edge colorings are one of several different types of graph coloring. The edge-coloring problem asks whether it is possible to color the edges of a given graph using at most k different colors, for a given value of k, or with the fewest possible colors. The minimum required number of colors for the edges of a given graph is called the chromatic index of the graph. For example, the edges of the graph in the illustration can be colored by three colors but cannot be colored by two colors, so the graph shown has chromatic index three.

In graph theory, a branch of mathematics, list coloring is a type of graph coloring where each vertex can be restricted to a list of allowed colors. It was first studied in the 1970s in independent papers by Vizing and by Erdős, Rubin, and Taylor.

<span class="mw-page-title-main">Snark (graph theory)</span> 3-regular graph with no 3-edge-coloring

In the mathematical field of graph theory, a snark is an undirected graph with exactly three edges per vertex whose edges cannot be colored with only three colors. In order to avoid trivial cases, snarks are often restricted to have additional requirements on their connectivity and on the length of their cycles. Infinitely many snarks exist.

<span class="mw-page-title-main">Hadwiger conjecture (graph theory)</span> Unproven generalization of the four-color theorem

In graph theory, the Hadwiger conjecture states that if is loopless and has no minor then its chromatic number satisfies . It is known to be true for . The conjecture is a generalization of the four-color theorem and is considered to be one of the most important and challenging open problems in the field.

In graph theory, Vizing's theorem states that every simple undirected graph may be edge colored using a number of colors that is at most one larger than the maximum degree Δ of the graph. At least Δ colors are always necessary, so the undirected graphs may be partitioned into two classes: "class one" graphs for which Δ colors suffice, and "class two" graphs for which Δ + 1 colors are necessary. A more general version of Vizing's theorem states that every undirected multigraph without loops can be colored with at most Δ+µ colors, where µ is the multiplicity of the multigraph. The theorem is named for Vadim G. Vizing who published it in 1964.

<span class="mw-page-title-main">Triangle-free graph</span> Graph without triples of adjacent vertices

In the mathematical area of graph theory, a triangle-free graph is an undirected graph in which no three vertices form a triangle of edges. Triangle-free graphs may be equivalently defined as graphs with clique number ≤ 2, graphs with girth ≥ 4, graphs with no induced 3-cycle, or locally independent graphs.

The discharging method is a technique used to prove lemmas in structural graph theory. Discharging is most well known for its central role in the proof of the four color theorem. The discharging method is used to prove that every graph in a certain class contains some subgraph from a specified list. The presence of the desired subgraph is then often used to prove a coloring result.

<span class="mw-page-title-main">Brooks' theorem</span>

In graph theory, Brooks' theorem states a relationship between the maximum degree of a graph and its chromatic number. According to the theorem, in a connected graph in which every vertex has at most Δ neighbors, the vertices can be colored with only Δ colors, except for two cases, complete graphs and cycle graphs of odd length, which require Δ + 1 colors.

<span class="mw-page-title-main">Greedy coloring</span> One-by-one assignment of colors to graph vertices

In the study of graph coloring problems in mathematics and computer science, a greedy coloring or sequential coloring is a coloring of the vertices of a graph formed by a greedy algorithm that considers the vertices of the graph in sequence and assigns each vertex its first available color. Greedy colorings can be found in linear time, but they do not, in general, use the minimum number of colors possible.

In computer science, lexicographic breadth-first search or Lex-BFS is a linear time algorithm for ordering the vertices of a graph. The algorithm is different from a breadth-first search, but it produces an ordering that is consistent with breadth-first search.

<span class="mw-page-title-main">Errera graph</span>

In the mathematical field of graph theory, the Errera graph is a graph with 17 vertices and 45 edges. Alfred Errera published it in 1921 as a counterexample to Kempe's erroneous proof of the four color theorem; it was named after Errera by Hutchinson & Wagon (1998).

<span class="mw-page-title-main">Degeneracy (graph theory)</span> Measurement of graph sparsity

In graph theory, a k-degenerate graph is an undirected graph in which every subgraph has a vertex of degree at most k: that is, some vertex in the subgraph touches k or fewer of the subgraph's edges. The degeneracy of a graph is the smallest value of k for which it is k-degenerate. The degeneracy of a graph is a measure of how sparse it is, and is within a constant factor of other sparsity measures such as the arboricity of a graph.

In graph theory, a mathematical discipline, coloring refers to an assignment of colours or labels to vertices, edges and faces of a graph. Defective coloring is a variant of proper vertex coloring. In a proper vertex coloring, the vertices are coloured such that no adjacent vertices have the same colour. In defective coloring, on the other hand, vertices are allowed to have neighbours of the same colour to a certain extent.

The Recursive Largest First (RLF) algorithm is a heuristic for the NP-hard graph coloring problem. It was originally proposed by Frank Leighton in 1979.

References

  1. Lipton, Richard J.; Miller, Raymond E. (1978), "A batching method for coloring planar graphs", Information Processing Letters, 7 (4): 185–188, doi:10.1016/0020-0190(78)90065-0, MR   0497394
  2. Chiba, Norishige; Nishizeki, Takao; Saito, Nobuji (1981), "A linear 5-coloring algorithm of planar graphs", Journal of Algorithms, 2 (4): 317–327, doi:10.1016/0196-6774(81)90031-6, MR   0640516
  3. Matula, David; Shiloach, Yossi; Tarjan, Robert (November 1980), Two linear-time algorithms for five-coloring a planar graph (PDF), Tech. Report STAN-CS-80-830, Stanford University
  4. Frederickson, Greg N. (1984), "On linear-time algorithms for five-coloring planar graphs", Information Processing Letters, 19 (5): 219–224, CiteSeerX   10.1.1.158.5812 , doi:10.1016/0020-0190(84)90056-5, MR   0777802
  5. Williams, M. H. (1985), "A linear algorithm for colouring planar graphs with five colours", The Computer Journal, 28 (1): 78–81, doi: 10.1093/comjnl/28.1.78 , MR   0786929
  6. Hagerup, Torben; Chrobak, Marek; Diks, Krzysztof (1989), "Optimal parallel 5-colouring of planar graphs", SIAM Journal on Computing, 18 (2): 288–300, doi:10.1137/0218020, MR   0986668
  7. Robertson, Neil; Sanders, Daniel P.; Seymour, Paul; Thomas, Robin (1996), "Efficiently four-coloring planar graphs" (PDF), Proc. 28th ACM Symposium on Theory of Computing (STOC) , New York: ACM Press.
  8. Kainen, Paul C. (September 1974). "A Generalization of the 5-Color Theorem" (PDF). Proceedings of the American Mathematical Society. 45 (3): 450–452. doi:10.2307/2039977.

Further reading