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Graph structure theorem

Graph structure theorem is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Graph structure theorem rather than just read about it. In short: In mathematics, the graph structure theorem is a major result in the area of graph theory. The result establishes a deep and fundamental connection between the theory of graph minors and topological embeddings.

Key takeaways

  • Graph structure theorem belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Graph structure theorem to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Graph structure theorem from memory before moving on to harder problems.

Reference excerpt

In mathematics, the graph structure theorem is a major result in the area of graph theory. The result establishes a deep and fundamental connection between the theory of graph minors and topological embeddings. The theorem is stated in the seventeenth of a series of 23 papers by Neil Robertson and Paul Seymour. Its proof is very long and involved. Kawarabayashi & Mohar (2007) and Lovász (2006) are surveys accessible to nonspecialists, describing the theorem and its consequences.

Setup and motivation for the theorem A minor of a graph G is any graph H that is isomorphic to a graph that can be obtained from a subgraph of G by contracting some edges. If G does not have a graph H as a minor, then we say that G is H-free. Let H be a fixed graph. Intuitively, if G is a huge H-free graph, then there ought to be a "good reason" for this. The graph structure theorem provides such a "good reason" in the form of a rough description of the structure of G. In essence, every H-free graph G suffers from one of two structural deficiencies: either G is "too thin" to have H as a minor, or G can be (almost) topologically embedded on a surface that is too simple to embed H upon. The first reason applies if H is a planar graph, and both reasons apply if H is not planar. We first make precise these notions.

Tree width The tree width of a graph G is a positive integer that specifies the "thinness" of G. For example, a connected graph G has tree width one if and only if it is a tree, and G has tree width two if and only if it is a series–parallel graph. Intuitively, a huge graph G has small tree width if and only if G takes the structure of a huge tree whose nodes and edges have been replaced by small graphs. We give a precise definition of tree width in the subsection regarding clique-sums. It is a theorem that if H is a minor of G, then the tree width of H is not greater than that of G. Therefore, one "good reason" for G to be H-free is that the tree width of G is not very large. The graph structure theorem implies that this reason always applies in case H is planar. Corollary 1. For every planar graph H, there exists a positive integer k such that every H-free graph has tree width less than k. It is unfortunate that the value of k in Corollary 1 is generally much larger than the tree width of H (a notable exception is when H = K4, the complete graph on four vertices, for which k = 3). This is one reason that the graph structure theorem is said to describe the "rough structure" of H-free graphs.

Surface embeddings Roughly, a surface is a set of points with a local topological structure of a disc. Surfaces fall into two infinite families: the orientable surfaces include the sphere, the torus, the double torus and so on; the nonorientable surfaces include the real projective plane, the Klein bottle and so on. A graph embeds on a surface if the graph can be drawn on the surface as a set of points (vertices) and arcs (edges) that do not cross or touch each other, except where edges and vertices are incident or adjacent. A graph is planar if it embeds on the sphere. If a graph G embeds on a particular surface then every minor of G also embeds on that same surface. Therefore, a "good reason" for G to be H-free is that G embeds on a surface that H does not embed on. When H is not planar, the graph structure theorem may be looked at as a vast generalization of the Kuratowski theorem. A version of this theorem proved by Wagner (1937) states that if a graph G is both K5-free and K3,3-free, then G is planar. This theorem provides a "good reason" for a graph G not to have K5 or K3,3 as minors; specifically, G embeds on the sphere, whereas neither K5 nor K3,3 embed on the sphere. Unfortunately, this notion of "good reason" is not sophisticated enough for the graph structure theorem. Two more notions are required: clique-sums and vortices.

Clique-sums A clique in a graph G is any set of vertices that are pairwise adjacent in G. For a non-negative integer k, a k-clique-sum of two graphs G and K is any graph obtained by selecting a non-negative integer m ≤ k, selecting clique of size m in each of G and K, identifying the two cliques into a single clique of size m, then deleting zero or more of the edges that join vertices in the new clique. If G1, G2, …, Gn is a list of graphs, then we may produce a new graph by joining the list of graphs via k-clique-sums. That is, we take a k-clique-sum of G1 and G2, then take a k-clique-sum of G3 with the resulting graph, and so on. A graph has tree width at most k if it can be obtained via k-clique-sums from a list of graphs, where each graph in the list has at most k + 1 vertices. Corollary 1 indicates to us that k-clique-sums of small graphs describe the rough structure H-free graphs when H is planar. When H is nonplanar, we also need to consider k-clique-sums of a list of graphs, each of which is embedded on a surface. The following example with H = K5 illustrates this point. The graph K5 embeds on every surface except for the sphere. However, there exist K5-free graphs that are far from planar. In particular, the 3-clique-sum of any list of planar graphs results in a K5-free graph. Wagner (1937) determined the precise structure of K5-free graphs, as part of a cluster of results known as Wagner's theorem: Theorem 2. If G is K5-free, then G can be obtained via 3-clique-sums from a list of planar graphs, and copies of one special non-planar graph having 8-vertices. We point out that Theorem 2 is an exact structure theorem since the precise structure of K5-free graphs is determined. Such results are rare within graph theory. The graph structure theorem is not precise in this sense because, for most graphs H, the structural description of H-free graphs includes some graphs that are not H-free.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Graph structure theorem

Start with the simplest possible case. Write down what Graph structure theorem claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Graph structure theorem before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Graph structure theorem ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Graph structure theorem

In research
Graph structure theorem appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Graph structure theorem in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Graph structure theorem is common in secondary-school and first-year university syllabi. It links to neighbouring topics Graph minor theory, Theorems in graph theory, so understanding it makes those chapters shorter.
In everyday life
Look for Graph structure theorem outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Graph structure theorem in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Graph structure theorem means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Graph structure theorem out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Graph structure theorem in simple terms?

In mathematics, the graph structure theorem is a major result in the area of graph theory. The result establishes a deep and fundamental connection between the theory of graph minors and topological embeddings.

Why does Graph structure theorem matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Graph structure theorem?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Graph structure theorem.

Tags

  • Graph minor theory
  • Theorems in graph theory

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