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Thickness (graph theory)

Thickness (graph theory) is a science 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 Thickness (graph theory) rather than just read about it. In short: In graph theory, the thickness of a graph G is the minimum number of planar graphs into which the edges of G can be partitioned. That is, if there exists a collection of k planar graphs, all having the same set of vertices, such that the union of these planar graphs is G, then the thickness of G is at most k.

Thickness (graph theory) — main illustration
Thickness (graph theory) — illustration

Key takeaways

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

Reference excerpt

In graph theory, the thickness of a graph G is the minimum number of planar graphs into which the edges of G can be partitioned. That is, if there exists a collection of k planar graphs, all having the same set of vertices, such that the union of these planar graphs is G, then the thickness of G is at most k. In other words, the thickness of a graph is the minimum number of planar subgraphs whose union equals to graph G. Thus, a planar graph has thickness one. Graphs of thickness two are called biplanar graphs. The concept of thickness originates in the Earth–Moon problem on the chromatic number of biplanar graphs, posed in 1959 by Gerhard Ringel, and on a related 1962 conjecture of Frank Harary: Every graph on nine points or its complementary graph is non-planar. The problem is equivalent to determining whether the complete graph K9 is biplanar (it is not, and the conjecture is true). A comprehensive survey on the state of the arts of the topic as of 1998 was written by Petra Mutzel, Thomas Odenthal and Mark Scharbrodt.

Specific graphs The thickness of the complete graph on n vertices, Kn, is

⌊ n + 7 6 ⌋ , {\displaystyle \left\lfloor {\frac {n+7}{6}}\right\rfloor ,}

except when n = 9, 10 for which the thickness is three. With some exceptions, the thickness of a complete bipartite graph Ka,b is generally:

⌈ a b 2 ( a + b − 2 ) ⌉ . {\displaystyle \left\lceil {\frac {ab}{2(a+b-2)}}\right\rceil .}

Properties Every forest is planar, and every planar graph can be partitioned into at most three forests. Therefore, the thickness of any graph G is at most equal to the arboricity of the same graph (the minimum number of forests into which it can be partitioned) and at least equal to the arboricity divided by three. The graphs of maximum degree d {\displaystyle d} have thickness at most ⌈ d / 2 ⌉ {\displaystyle \lceil d/2\rceil } . This cannot be improved: for a d {\displaystyle d} -regular graph with girth at least 2 d {\displaystyle 2d} , the high girth forces any planar subgraph to be sparse, causing its thickness to be exactly ⌈ d / 2 ⌉ {\displaystyle \lceil d/2\rceil } .

Graphs of thickness t {\displaystyle t} with n {\displaystyle n} vertices have at most t ( 3 n − 6 ) {\displaystyle t(3n-6)} edges. Because this gives them average degree less than 6 t {\displaystyle 6t} , their degeneracy is at most 6 t − 1 {\displaystyle 6t-1} and their chromatic number is at most 6 t {\displaystyle 6t} . Here, the degeneracy can be defined as the maximum, over subgraphs of the given graph, of the minimum degree within the subgraph. In the other direction, if a graph has degeneracy D {\displaystyle D} then its arboricity and thickness are at most D {\displaystyle D} . One can find an ordering of the vertices of the graph in which each vertex has at most D {\displaystyle D} neighbors that come later than it in the ordering, and assigning these edges to D {\displaystyle D} distinct subgraphs produces a partition of the graph into D {\displaystyle D} trees, which are planar graphs. Even in the case t = 2 {\displaystyle t=2} , the precise value of the chromatic number is unknown; this is Gerhard Ringel's Earth–Moon problem. An example of Thom Sulanke shows that, for t = 2 {\displaystyle t=2} , at least 9 colors are needed.

Related problems Thickness is closely related to the problem of simultaneous embedding. If two or more planar graphs all share the same vertex set, then it is possible to embed all these graphs in the plane, with the edges drawn as curves, so that each vertex has the same position in all the different drawings. However, it may not be possible to construct such a drawing while keeping the edges drawn as straight line segments. A different graph invariant, the rectilinear thickness or geometric thickness of a graph G, counts the smallest number of planar graphs into which G can be decomposed subject to the restriction that all of these graphs can be drawn simultaneously with straight edges. The book thickness adds an additional restriction, that all of the vertices be drawn in convex position, forming a circular layout of the graph. However, in contrast to the situation for arboricity and degeneracy, no two of these three thickness parameters are always within a constant factor of each other.

Computational complexity It is NP-hard to compute the thickness of a given graph, and NP-complete to test whether the thickness is at most two. However, the connection to arboricity allows the thickness to be approximated to within an approximation ratio of 3 in polynomial time.

References

Worked examples

Example 1 — a first encounter with Thickness (graph theory)

Start with the simplest possible case. Write down what Thickness (graph theory) claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, 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 Thickness (graph theory) 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 Thickness (graph theory) 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 Thickness (graph theory)

In research
Thickness (graph theory) appears in science 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 Thickness (graph theory) 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
Thickness (graph theory) is common in secondary-school and first-year university syllabi. It links to neighbouring topics Graph invariants, NP-complete problems, Planar graphs, so understanding it makes those chapters shorter.
In everyday life
Look for Thickness (graph theory) 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 Thickness (graph theory) in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Thickness (graph theory) 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 Thickness (graph theory) out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Thickness (graph theory) in simple terms?

In graph theory, the thickness of a graph G is the minimum number of planar graphs into which the edges of G can be partitioned. That is, if there exists a collection of k planar graphs, all having the same set of vertices, such that the union of these planar graphs is G, then the thickness of G is…

Why does Thickness (graph theory) matter?

Because it connects several science 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 Thickness (graph theory)?

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 Thickness (graph theory).

Tags

  • Graph invariants
  • NP-complete problems
  • Planar graphs

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