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Graph amalgamation

Graph amalgamation 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 Graph amalgamation rather than just read about it. In short: In graph theory, a graph amalgamation is a relationship between two graphs (one graph is an amalgamation of another). Similar relationships include subgraphs and minors.

Graph amalgamation — main illustration
Graph amalgamation — illustration

Key takeaways

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

Reference excerpt

In graph theory, a graph amalgamation is a relationship between two graphs (one graph is an amalgamation of another). Similar relationships include subgraphs and minors. Amalgamations can provide a way to reduce a graph to a simpler graph while keeping certain structure intact. The amalgamation can then be used to study properties of the original graph in an easier to understand context. Applications include embeddings, computing genus distribution, and Hamiltonian decompositions.

Definition Let G {\displaystyle G} and H {\displaystyle H} be two graphs with the same number of edges where G {\displaystyle G} has more vertices than H {\displaystyle H} . Then we say that H {\displaystyle H} is an amalgamation of G {\displaystyle G} if there is a bijection ϕ : E ( G ) → E ( H ) {\displaystyle \phi :E(G)\to E(H)} and a surjection ψ : V ( G ) → V ( H ) {\displaystyle \psi :V(G)\to V(H)} and the following hold:

If x {\displaystyle x} , y {\displaystyle y} are two vertices in G {\displaystyle G} where ψ ( x ) ≠ ψ ( y ) {\displaystyle \psi (x)\neq \psi (y)} , and both x {\displaystyle x} and y {\displaystyle y} are adjacent by edge e {\displaystyle e} in G {\displaystyle G} , then ψ ( x ) {\displaystyle \psi (x)} and ψ ( y ) {\displaystyle \psi (y)} are adjacent by edge ϕ ( e ) {\displaystyle \phi (e)} in H {\displaystyle H} . If e {\displaystyle e} is a loop on a vertex x ∈ V ( G ) {\displaystyle x\in V(G)} , then ϕ ( e ) {\displaystyle \phi (e)} is a loop on ψ ( x ) ∈ H {\displaystyle \psi (x)\in H} . If e {\displaystyle e} joins x , y ∈ V ( G ) {\displaystyle x,y\in V(G)} , where x ≠ y {\displaystyle x\neq y} , but ψ ( x ) = ψ ( y ) {\displaystyle \psi (x)=\psi (y)} , then ϕ ( e ) {\displaystyle \phi (e)} is a loop on ψ ( x ) {\displaystyle \psi (x)} . Note that while G {\displaystyle G} can be a graph or a pseudograph, it will usually be the case that H {\displaystyle H} is a pseudograph.

Properties Edge colorings are invariant to amalgamation. This is obvious, as all of the edges between the two graphs are in bijection with each other. However, what may not be obvious, is that if G {\displaystyle G} is a complete graph of the form K 2 n + 1 {\displaystyle K_{2n+1}} , and we color the edges as to specify a Hamiltonian decomposition (a decomposition into Hamiltonian paths), then those edges also form a Hamiltonian Decomposition in H {\displaystyle H} .

Example

Figure 1 illustrates an amalgamation of K 5 {\displaystyle K_{5}} . The invariance of edge coloring and Hamiltonian Decomposition can be seen clearly. The function ϕ {\displaystyle \phi } is a bijection and is given as letters in the figure. The function ψ {\displaystyle \psi } is given in the table below.

Hamiltonian decompositions One of the ways in which amalgamations can be used is to find Hamiltonian Decompositions of complete graphs with 2n + 1 vertices. The idea is to take a graph and produce an amalgamation of it which is edge colored in n {\displaystyle n} colors and satisfies certain properties (called an outline Hamiltonian decomposition). We can then 'reverse' the amalgamation and we are left with K 2 n + 1 {\displaystyle K_{2n+1}} colored in a Hamiltonian Decomposition. In Hilton outlines a method for doing this, as well as a method for finding all Hamiltonian Decompositions without repetition. The methods rely on a theorem he provides which states (roughly) that if we have an outline Hamiltonian decomposition, we could have arrived at it by first starting with a Hamiltonian decomposition of the complete graph and then finding an amalgamation for it.

Notes

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Graph amalgamation

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

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

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

Frequently asked questions

What is Graph amalgamation in simple terms?

In graph theory, a graph amalgamation is a relationship between two graphs (one graph is an amalgamation of another). Similar relationships include subgraphs and minors.

Why does Graph amalgamation 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 Graph amalgamation?

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 amalgamation.

Tags

  • Graph theory

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