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Neighbourhood (graph theory)

Neighbourhood (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 Neighbourhood (graph theory) rather than just read about it. In short: In graph theory, the neighbourhood of a vertex v in a graph G is the subgraph of G induced by all the vertices that are connected to v by an edge (vertices that are adjacent to v), i.e., the graph composed of all the vertices adjacent to v and all the edges connecting them. The neighbourhood is often denoted by ⁠ N G ( v ) {\displaystyle N_{G}(v)} ⁠ or (when the graph is unambiguous) ⁠ N ( v ) {\displaystyle N(v)} ⁠.

Neighbourhood (graph theory) — main illustration
Neighbourhood (graph theory) — illustration

Key takeaways

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

Reference excerpt

In graph theory, the neighbourhood of a vertex v in a graph G is the subgraph of G induced by all the vertices that are connected to v by an edge (vertices that are adjacent to v), i.e., the graph composed of all the vertices adjacent to v and all the edges connecting them. The neighbourhood is often denoted by ⁠ N G ( v ) {\displaystyle N_{G}(v)} ⁠ or (when the graph is unambiguous) ⁠ N ( v ) {\displaystyle N(v)} ⁠. The same neighbourhood notation may also be used to refer to the set of adjacent vertices rather than the corresponding induced subgraph. The neighbourhood described above does not include v itself, and is more specifically the open neighbourhood of v; it is also possible to define a neighbourhood in which v itself is included, called the closed neighbourhood of v and denoted by ⁠ N G [ v ] {\displaystyle N_{G}[v]} ⁠. When stated without any qualification, a neighbourhood is assumed to be open. Neighbourhoods may be used to represent graphs in computer algorithms, via the adjacency list and adjacency matrix representations. Neighbourhoods are also used in the clustering coefficient of a graph, which is a measure of the average density of its neighbourhoods. In addition, many important classes of graphs may be defined by properties of their neighbourhoods, or by symmetries that relate neighbourhoods to each other. An isolated vertex has no adjacent vertex. The degree of a vertex v is the number of vertices adjacent to v. A special case is a loop, i.e., an edge that connects a vertex to itself; if such an edge exists, then the vertex belongs to its own neighbourhood.

Local properties in graphs

If all vertices in G have neighbourhoods that are isomorphic to the same graph H, G is said to be locally H, and if all vertices in G have neighbourhoods that belong to some graph family F, G is said to be locally F. For instance, in the octahedron graph, shown in the figure, each vertex has a neighbourhood isomorphic to a cycle of four vertices, so the octahedron is locally C4. For example:

Any complete graph Kn is locally Kn−1. The only graphs that are locally complete are disjoint unions of complete graphs. A Turán graph T(rs,r) is locally T((r−1)s,r−1). More generally, any Turán graph is locally Turán. Every planar graph is locally outerplanar. However, not every locally outerplanar graph is planar. A graph is triangle-free if and only if it is locally independent. Every k-chromatic graph is locally (k−1)-chromatic. Every locally k-chromatic graph has chromatic number O ( k n ) {\displaystyle O({\sqrt {kn}})} . If a graph family F is closed under the operation of taking induced subgraphs, then every graph in F is also locally F. For instance, every chordal graph is locally chordal; every perfect graph is locally perfect; every comparability graph is locally comparable; every (k)-(ultra)-homogeneous graph is locally (k)-(ultra)-homogeneous. A graph is locally cyclic if every neighbourhood is a cycle. For instance, the octahedron is the unique connected locally C4 graph, the icosahedron is the unique connected locally C5 graph, and the Paley graph of order 13 is locally C6. Locally cyclic graphs other than K4 are exactly the underlying graphs of Whitney triangulations, embeddings of graphs on surfaces in such a way that the faces of the embedding are the cliques of the graph. Locally cyclic graphs can have as many as n 2 − o ( 1 ) {\displaystyle n^{2-o(1)}} edges. Claw-free graphs are the graphs that are locally co-triangle-free; that is, for all vertices, the complement graph of the neighbourhood of the vertex does not contain a triangle. A graph that is locally H is claw-free if and only if the independence number of H is at most two; for instance, the graph of the regular icosahedron is claw-free because it is locally C5 and C5 has independence number two. The locally linear graphs are the graphs in which every neighbourhood is an induced matching. The Johnson graphs are locally grid, meaning that each neighborhood is a rook's graph.

Neighbourhood of a set For a set A of vertices, the neighbourhood of A is the union of the neighbourhoods of the vertices, and so it is the set of all vertices adjacent to at least one member of A. A set A of vertices in a graph is said to be a module if every vertex in A has the same set of neighbours outside of A. Any graph has a uniquely recursive decomposition into modules, its modular decomposition, which can be constructed from the graph in linear time; modular decomposition algorithms have applications in other graph algorithms including the recognition of comparability graphs.

See also Markov blanket Moore neighbourhood Von Neumann neighbourhood Second neighborhood problem Vertex figure, a related concept in polyhedra Link (simplicial complex), a generalization of the neighborhood to simplicial complexes

Notes

… excerpt ends here. Continue reading the full article.

Illustrations

Neighbourhood (graph theory): In this graph, the vertices adjacent to 5 are 1, 2, and 4. The neighbourhood of 5 is the graph consisting of the vertices 1, 2, 4, and the edge connecting 1 and 2.
In this graph, the vertices adjacent to 5 are 1, 2, and 4. The neighbourhood of 5 is the graph consisting of the vertices 1, 2, 4, and the edge connecting 1 and 2.
Neighbourhood (graph theory): In the octahedron graph, the neighbourhood of any vertex is a 4-cycle.
In the octahedron graph, the neighbourhood of any vertex is a 4-cycle.

Worked examples

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

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

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

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

Frequently asked questions

What is Neighbourhood (graph theory) in simple terms?

In graph theory, the neighbourhood of a vertex v in a graph G is the subgraph of G induced by all the vertices that are connected to v by an edge (vertices that are adjacent to v), i.e., the graph composed of all the vertices adjacent to v and all the edges connecting them. The neighbourhood is oft…

Why does Neighbourhood (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 Neighbourhood (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 Neighbourhood (graph theory).

Tags

  • Graph theory objects

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