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Graph automorphism

Graph automorphism 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 automorphism rather than just read about it. In short: In the mathematical field of graph theory, an automorphism of a graph is a form of symmetry in which the graph is mapped onto itself while preserving the edge–vertex connectivity. Formally, an automorphism of a graph G = (V, E) is a permutation σ of the vertex set V, such that the pair of vertices (u, v) form an edge if and only if the pair (σ(u), σ(v)) also form an edge.

Graph automorphism — main illustration
Graph automorphism — illustration

Key takeaways

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

Reference excerpt

In the mathematical field of graph theory, an automorphism of a graph is a form of symmetry in which the graph is mapped onto itself while preserving the edge–vertex connectivity. Formally, an automorphism of a graph G = (V, E) is a permutation σ of the vertex set V, such that the pair of vertices (u, v) form an edge if and only if the pair (σ(u), σ(v)) also form an edge. That is, it is a graph isomorphism from G to itself. Automorphisms may be defined in this way both for directed graphs and for undirected graphs. The composition of two automorphisms is another automorphism, and the set of automorphisms of a given graph, under the composition operation, forms a group, the automorphism group of the graph. In the opposite direction, by Frucht's theorem, all groups can be represented as the automorphism group of a connected graph – indeed, of a cubic graph.

Computational complexity Constructing the automorphism group of a graph, in the form of a list of generators, is polynomial-time equivalent to the graph isomorphism problem, and therefore solvable in quasi-polynomial time, that is with running time 2 O ( ( log ⁡ n ) c ) {\displaystyle 2^{O((\log n)^{c})}} for some fixed c > 0 {\displaystyle c>0} . Consequently, like the graph isomorphism problem, the problem of finding a graph's automorphism group is known to belong to the complexity class NP, but not known to be in P nor to be NP-complete, and therefore may be NP-intermediate.

The easier problem of testing whether a graph has any symmetries (nontrivial automorphisms), known as the graph automorphism problem, also has no known polynomial time solution. There is a polynomial time algorithm for solving the graph automorphism problem for graphs where vertex degrees are bounded by a constant. The graph automorphism problem is polynomial-time many-one reducible to the graph isomorphism problem, but the converse reduction is unknown. By contrast, hardness is known when the automorphisms are constrained in a certain fashion; for instance, determining the existence of a fixed-point-free automorphism (an automorphism that fixes no vertex) is NP-complete, and the problem of counting such automorphisms is ♯P-complete.

Algorithms, software and applications While no worst-case polynomial-time algorithms are known for the general Graph Automorphism problem, finding the automorphism group (and printing out an irredundant set of generators) for many large graphs arising in applications is rather easy. Several open-source software tools are available for this task, including NAUTY, BLISS and SAUCY. SAUCY and BLISS are particularly efficient for sparse graphs, e.g., SAUCY processes some graphs with millions of vertices in mere seconds. However, BLISS and NAUTY can also produce Canonical Labeling, whereas SAUCY is currently optimized for solving Graph Automorphism. An important observation is that for a graph on n vertices, the automorphism group can be specified by no more than n − 1 {\displaystyle n-1} generators, and the above software packages are guaranteed to satisfy this bound as a side-effect of their algorithms (minimal sets of generators are harder to find and are not particularly useful in practice). It also appears that the total support (i.e., the number of vertices moved) of all generators is limited by a linear function of n, which is important in runtime analysis of these algorithms. However, this has not been established for a fact, as of March 2012. Practical applications of Graph Automorphism include graph drawing and other visualization tasks, solving structured instances of Boolean Satisfiability arising in the context of Formal verification and Logistics. Molecular symmetry can predict or explain chemical properties.

Symmetry display Several graph drawing researchers have investigated algorithms for drawing graphs in such a way that the automorphisms of the graph become visible as symmetries of the drawing. This may be done either by using a method that is not designed around symmetries, but that automatically generates symmetric drawings when possible, or by explicitly identifying symmetries and using them to guide vertex placement in the drawing. It is not always possible to display all symmetries of the graph simultaneously, so it may be necessary to choose which symmetries to display and which to leave unvisualized.

Graph families defined by their automorphisms Several families of graphs are defined by having certain types of automorphisms:

An asymmetric graph is an undirected graph with only the trivial automorphism. A vertex-transitive graph is an undirected graph in which every vertex may be mapped by an automorphism into any other vertex. An edge-transitive graph is an undirected graph in which every edge may be mapped by an automorphism into any other edge. A symmetric graph is a graph such that every pair of adjacent vertices may be mapped by an automorphism into any other pair of adjacent vertices. A distance-transitive graph is a graph such that every pair of vertices may be mapped by an automorphism into any other pair of vertices that are the same distance apart. A semi-symmetric graph is a graph that is edge-transitive but not vertex-transitive. A half-transitive graph is a graph that is vertex-transitive and edge-transitive but not symmetric. A skew-symmetric graph is a directed graph together with a permutation σ on the vertices that maps edges to edges but reverses the direction of each edge. Additionally, σ is required to be an involution. Inclusion relationships between these families are indicated by the following table:

See also Algebraic graph theory Distinguishing coloring

References

External links Weisstein, Eric W. "Graph automorphism". MathWorld.

Illustrations

Graph automorphism: Skeleton of the dodecahedron
Skeleton of the dodecahedron
Graph automorphism: Shrikhande graph
Shrikhande graph
Graph automorphism: Paley graph
Paley graph
Graph automorphism: F26A graph
F26A graph
Graph automorphism: Nauru graph
Nauru graph

Worked examples

Example 1 — a first encounter with Graph automorphism

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

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

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

Frequently asked questions

What is Graph automorphism in simple terms?

In the mathematical field of graph theory, an automorphism of a graph is a form of symmetry in which the graph is mapped onto itself while preserving the edge–vertex connectivity. Formally, an automorphism of a graph G = (V, E) is a permutation σ of the vertex set V, such that the pair of vertices…

Why does Graph automorphism 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 automorphism?

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 automorphism.

Tags

  • Algebraic graph theory

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