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Graph embedding

Graph embedding 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 embedding rather than just read about it. In short: In topological graph theory, an embedding (also spelled imbedding) of a graph G {\displaystyle G} on a surface Σ {\displaystyle \Sigma } is a representation of G {\displaystyle G} on Σ {\displaystyle \Sigma } in which points of Σ {\displaystyle \Sigma } are associated with vertices and simple arcs (homeomorphic images of [ 0 , 1 ] {\displaystyle [0,1]} ) are associated with edges in such a way that: the endpoints of…

Graph embedding — main illustration
Graph embedding — illustration

Key takeaways

  • Graph embedding 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 embedding to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Graph embedding from memory before moving on to harder problems.

Reference excerpt

In topological graph theory, an embedding (also spelled imbedding) of a graph G {\displaystyle G} on a surface Σ {\displaystyle \Sigma } is a representation of G {\displaystyle G} on Σ {\displaystyle \Sigma } in which points of Σ {\displaystyle \Sigma } are associated with vertices and simple arcs (homeomorphic images of [ 0 , 1 ] {\displaystyle [0,1]} ) are associated with edges in such a way that:

the endpoints of the arc associated with an edge e {\displaystyle e} are the points associated with the end vertices of e , {\displaystyle e,}

no arcs include points associated with other vertices, two arcs never intersect at a point which is interior to either of the arcs. Here a surface is a connected 2 {\displaystyle 2} -manifold. Informally, an embedding of a graph into a surface is a drawing of the graph on the surface in such a way that its edges may intersect only at their endpoints. It is well known that any finite graph can be embedded in 3-dimensional Euclidean space R 3 {\displaystyle \mathbb {R} ^{3}} . A planar graph is one that can be embedded in 2-dimensional Euclidean space R 2 . {\displaystyle \mathbb {R} ^{2}.}

Often, an embedding is regarded as an equivalence class (under homeomorphisms of Σ {\displaystyle \Sigma } ) of representations of the kind just described. Some authors define a weaker version of the definition of "graph embedding" by omitting the non-intersection condition for edges. In such contexts the stricter definition is described as "non-crossing graph embedding". This article deals only with the strict definition of graph embedding. The weaker definition is discussed in the articles "graph drawing" and "crossing number".

Terminology If a graph G {\displaystyle G} is embedded on a closed surface Σ {\displaystyle \Sigma } , the complement of the union of the points and arcs associated with the vertices and edges of G {\displaystyle G} is a family of regions (or faces). A 2-cell embedding, cellular embedding or map is an embedding in which every face is homeomorphic to an open disk. A closed 2-cell embedding is an embedding in which the closure of every face is homeomorphic to a closed disk. The genus of a graph is the minimal integer n {\displaystyle n} such that the graph can be embedded in a surface of genus n {\displaystyle n} . In particular, a planar graph has genus 0 {\displaystyle 0} , because it can be drawn on a sphere without self-crossing. A graph that can be embedded on a torus is called a toroidal graph. The non-orientable genus of a graph is the minimal integer n {\displaystyle n} such that the graph can be embedded in a non-orientable surface of (non-orientable) genus n {\displaystyle n} . The Euler genus of a graph is the minimal integer n {\displaystyle n} such that the graph can be embedded in an orientable surface of (orientable) genus n / 2 {\displaystyle n/2} or in a non-orientable surface of (non-orientable) genus n {\displaystyle n} . A graph is orientably simple if its Euler genus is smaller than its non-orientable genus. The maximum genus of a graph is the maximal integer n {\displaystyle n} such that the graph can be 2 {\displaystyle 2} -cell embedded in an orientable surface of genus n {\displaystyle n} .

Combinatorial embedding

An embedded graph uniquely defines cyclic orders of edges incident to the same vertex. The set of all these cyclic orders is called a rotation system. Embeddings with the same rotation system are considered to be equivalent and the corresponding equivalence class of embeddings is called combinatorial embedding (as opposed to the term topological embedding, which refers to the previous definition in terms of points and curves). Sometimes, the rotation system itself is called a "combinatorial embedding". An embedded graph also defines natural cyclic orders of edges which constitutes the boundaries of the faces of the embedding. However handling these face-based orders is less straightforward, since in some cases some edges may be traversed twice along a face boundary. For example this is always the case for embeddings of trees, which have a single face. To overcome this combinatorial nuisance, one may consider that every edge is "split" lengthwise in two "half-edges", or "sides". Under this convention in all face boundary traversals each half-edge is traversed only once and the two half-edges of the same edge are always traversed in opposite directions. Other equivalent representations for cellular embeddings include the ribbon graph, a topological space formed by gluing together topological disks for the vertices and edges of an embedded graph, and the graph-encoded map, an edge-colored cubic graph with four vertices for each edge of the embedded graph.

… excerpt ends here. Continue reading the full article.

Illustrations

Graph embedding: The Heawood graph and associated map embedded in the torus.
The Heawood graph and associated map embedded in the torus.
Graph embedding illustration
Graph embedding illustration
Graph embedding illustration

Worked examples

Example 1 — a first encounter with Graph embedding

Start with the simplest possible case. Write down what Graph embedding 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 embedding 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 embedding 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 embedding

In research
Graph embedding 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 embedding 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 embedding is common in secondary-school and first-year university syllabi. It links to neighbouring topics Graph algorithms, Topological graph theory, so understanding it makes those chapters shorter.
In everyday life
Look for Graph embedding 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 embedding in 20 minutes

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

Frequently asked questions

What is Graph embedding in simple terms?

In topological graph theory, an embedding (also spelled imbedding) of a graph G {\displaystyle G} on a surface Σ {\displaystyle \Sigma } is a representation of G {\displaystyle G} on Σ {\displaystyle \Sigma } in which points of Σ {\displaystyle \Sigma } are associated with vertices and simple arcs…

Why does Graph embedding 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 embedding?

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 embedding.

Tags

  • Graph algorithms
  • Topological graph theory

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