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Girth (graph theory)

Girth (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 Girth (graph theory) rather than just read about it. In short: In graph theory, the girth of an undirected graph is the length of a shortest cycle contained in the graph. If the graph does not contain any cycles (that is, it is a forest), its girth is defined to be infinity.

Girth (graph theory) — main illustration
Girth (graph theory) — illustration

Key takeaways

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

Reference excerpt

In graph theory, the girth of an undirected graph is the length of a shortest cycle contained in the graph. If the graph does not contain any cycles (that is, it is a forest), its girth is defined to be infinity. For example, a 4-cycle (square) has girth 4. A grid has girth 4 as well, and a triangular mesh has girth 3. A graph with girth four or more is triangle-free.

Cages

A cubic graph (all vertices have degree three) of girth g that is as small as possible is known as a g-cage (or as a (3,g)-cage). The Petersen graph is the unique 5-cage (it is the smallest cubic graph of girth 5), the Heawood graph is the unique 6-cage, the McGee graph is the unique 7-cage and the Tutte eight cage is the unique 8-cage. There may exist multiple cages for a given girth. For instance there are three nonisomorphic 10-cages, each with 70 vertices: the Balaban 10-cage, the Harries graph and the Harries–Wong graph.

Girth and graph coloring For any positive integers g and χ, there exists a graph with girth at least g and chromatic number at least χ; for instance, the Grötzsch graph is triangle-free and has chromatic number 4, and repeating the Mycielskian construction used to form the Grötzsch graph produces triangle-free graphs of arbitrarily large chromatic number. Paul Erdős was the first to prove the general result, using the probabilistic method. More precisely, he showed that a random graph on n vertices, formed by choosing independently whether to include each edge with probability n(1–g)/g, has, with probability tending to 1 as n goes to infinity, at most ⁠n/2⁠ cycles of length g or less, but has no independent set of size ⁠n/2k ⁠. Therefore, removing one vertex from each short cycle leaves a smaller graph with girth greater than g, in which each color class of a coloring must be small and which therefore requires at least k colors in any coloring. Explicit, though large, graphs with high girth and chromatic number can be constructed as certain Cayley graphs of linear groups over finite fields. These remarkable Ramanujan graphs also have large expansion coefficient.

Related concepts The odd girth and even girth of a graph are the lengths of a shortest odd cycle and shortest even cycle respectively. The circumference of a graph is the length of the longest (simple) cycle, rather than the shortest. Thought of as the least length of a non-trivial cycle, the girth admits natural generalisations as the 1-systole or higher systoles in systolic geometry. Girth is the dual concept to edge connectivity, in the sense that the girth of a planar graph is the edge connectivity of its dual graph, and vice versa. These concepts are unified in matroid theory by the girth of a matroid, the size of the smallest dependent set in the matroid. For a graphic matroid, the matroid girth equals the girth of the underlying graph, while for a co-graphic matroid it equals the edge connectivity.

Computation The girth of an undirected graph can be computed by running a breadth-first search from each node, with complexity O ( n m ) {\displaystyle O(nm)} where n {\displaystyle n} is the number of vertices of the graph and m {\displaystyle m} is the number of edges. A practical optimization is to limit the depth of the BFS to a depth that depends on the length of the smallest cycle discovered so far. Better algorithms are known in the case where the girth is even and when the graph is planar. In terms of lower bounds, computing the girth of a graph is at least as hard as solving the triangle finding problem on the graph.

References

Illustrations

Girth (graph theory) illustration
Girth (graph theory) illustration
Girth (graph theory) illustration

Worked examples

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

Start with the simplest possible case. Write down what Girth (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 Girth (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 Girth (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 Girth (graph theory)

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

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

Frequently asked questions

What is Girth (graph theory) in simple terms?

In graph theory, the girth of an undirected graph is the length of a shortest cycle contained in the graph. If the graph does not contain any cycles (that is, it is a forest), its girth is defined to be infinity.

Why does Girth (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 Girth (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 Girth (graph theory).

Tags

  • Graph invariants

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