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In
graph theory In mathematics and computer science, graph theory is the study of ''graph (discrete mathematics), graphs'', which are mathematical structures used to model pairwise relations between objects. A graph in this context is made up of ''Vertex (graph ...
, a graph product is a
binary operation In mathematics, a binary operation or dyadic operation is a rule for combining two elements (called operands) to produce another element. More formally, a binary operation is an operation of arity two. More specifically, a binary operation ...
on
graph Graph may refer to: Mathematics *Graph (discrete mathematics), a structure made of vertices and edges **Graph theory, the study of such graphs and their properties *Graph (topology), a topological space resembling a graph in the sense of discret ...
s. Specifically, it is an operation that takes two graphs and and produces a graph with the following properties: * The vertex set of is the
Cartesian product In mathematics, specifically set theory, the Cartesian product of two sets and , denoted , is the set of all ordered pairs where is an element of and is an element of . In terms of set-builder notation, that is A\times B = \. A table c ...
, where and are the vertex sets of and , respectively. * Two vertices and of are connected by an edge,
iff In logic and related fields such as mathematics and philosophy, "if and only if" (often shortened as "iff") is paraphrased by the biconditional, a logical connective between statements. The biconditional is true in two cases, where either both ...
a condition about in and in is fulfilled. The graph products differ in what exactly this condition is. It is always about whether or not the vertices in are equal or connected by an edge. The terminology and notation for specific graph products in the literature varies quite a lot; even if the following may be considered somewhat standard, readers are advised to check what definition a particular author uses for a graph product, especially in older texts. Even for more standard definitions, it is not always consistent in the literature how to handle self-loops. The formulas below for the number of edges in a product also may fail when including self-loops. For example, the tensor product of a single vertex self-loop with itself is another single vertex self-loop with E=1, and not E=2 as the formula E_ = 2 E_ E_ would suggest.


Overview table

The following table shows the most common graph products, with \sim denoting "is connected by an edge to", and \not\sim denoting non-adjacency. While \not\sim ''does'' allow equality, \not\simeq means they must be distinct and non-adjacent. The operator symbols listed here are by no means standard, especially in older papers. In general, a graph product is determined by any condition for (a_1, a_2) \sim (b_1, b_2) that can be expressed in terms of a_n = b_n and a_n \sim b_n.


Mnemonic

Let K_2 be the complete graph on two vertices (i.e. a single edge). The product graphs K_2 \square K_2, K_2 \times K_2, and K_2 \boxtimes K_2 look exactly like the graph representing the operator. For example, K_2 \square K_2 is a four cycle (a square) and K_2 \boxtimes K_2 is the complete graph on four vertices. The G_1 _2/math> notation for lexicographic product serves as a reminder that this product is not commutative. The resulting graph looks like substituting a copy of G_2 for every vertex of G_1.


See also

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Graph operations In the mathematical field of graph theory, graph operations are operations which produce new graphs from initial ones. They include both unary (one input) and binary (two input) operations. Unary operations Unary operations create a new gra ...


Notes


References

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