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{{short description|Graph with same nodes but opposite connections as another}}
[[File:Petersen graph complement.svg|thumb|upright=1.35|The [[Petersen graph]] (on the left) and its complement graph (on the right).]]
In the [[mathematical]] field of [[graph theory]], the '''complement''' or '''inverse''' of a [[Graph (discrete mathematics)|graph]]
| last1=Bondy | first1=John Adrian | authorlink1=John Adrian Bondy▼
| last1=Bondy
| last2=Murty | first2=U. S. R. | authorlink2=U. S. R. Murty▼
| first1=John Adrian
| last2=Murty
| first2=U. S. R.
| title=Graph Theory with Applications
| year=1976
| publisher=North-Holland
| isbn=0-444-19451-7
| url=https://archive.org/details/graphtheorywitha0000bond/page/6
| page=[https://archive.org/details/graphtheorywitha0000bond/page/6 6]
| page = 6}}.</ref> It is not, however, the [[complement (set theory)|set complement]] of the graph; only the edges are complemented.▼
▲
==Definition==
Let {{math|1=''G'' = (''V'', ''E'')}} be a [[simple graph]] and let {{mvar|K}} consist of all 2-element subsets of {{mvar|V}}. Then {{math|1=''H'' = (''V'', ''K'' \ ''E'')}} is the complement of {{mvar|G}}
| last=Diestel | first=Reinhard
| title=Graph Theory
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| edition=3rd
| isbn=3-540-26182-6
}}. [http://diestel-graph-theory.com/index.html Electronic edition], page 4.</ref> where {{math|''K'' \ ''E''}} is the [[relative complement]] of {{mvar|E}} in {{mvar|K}}. For [[directed graph]]s, the complement can be defined in the same way, as a directed graph on the same vertex set, using the set of all 2-element [[ordered pair]]s of {{mvar|V}} in place of the set {{mvar|K}} in the formula above. In terms of the [[adjacency matrix]] ''A'' of the graph, if ''Q'' is the adjacency matrix of the [[complete graph]] of the same number of vertices (i.e. all entries are unity except the diagonal entries which are zero), then the adjacency matrix of the complement of ''A'' is ''Q-A''.
The complement is not defined for [[multigraph]]s. In graphs that allow [[loop (graph theory)|self-loops]] (but not multiple adjacencies) the complement of {{mvar|G}} may be defined by adding a self-loop to every vertex that does not have one in {{mvar|G}}, and otherwise using the same formula as above. This operation is, however, different from the one for simple graphs, since applying it to a graph with no self-loops would result in a graph with self-loops on all vertices.
==Applications and examples==
▲Several graph-theoretic concepts are related to each other via complement graphs:
*The complement of an [[edgeless graph]] is a [[complete graph]] and vice versa.
*Any [[induced subgraph]] of the complement graph of a graph {{mvar|G}} is the complement of the corresponding induced subgraph in {{mvar|G}}.
*An [[independent set (graph theory)|independent set]] in a graph is a [[clique (graph theory)|clique]] in the complement graph and vice versa. This is a special case of the previous two properties, as an independent set is an edgeless induced subgraph and a clique is a complete induced subgraph.
*The [[Graph automorphism|automorphism]] group of a graph is the automorphism group of its complement.
*The complement of every [[triangle-free graph]] is a [[claw-free graph]],<ref>{{Citation
| last1 = Chudnovsky | first1 = Maria | author1-link = Maria Chudnovsky
Line 43 ⟶ 49:
| contribution-url = http://www.math.princeton.edu/~mchudnov/claws_survey.pdf
| volume = 327
| year = 2005}}
| last1 = Bailey | first1 = Robert F.▼
| last2 = Cáceres | first2 = José▼
| doi = 10.1016/j.ejc.2012.10.008▼
| issue = 4▼
| mr = 3010114▼
| pages = 736–751▼
| volume = 34▼
▲ | year = 2013}}.</ref>
==Self-complementary graphs and graph classes==
[[File:Self-complementary NZ graph.svg|thumb|upright=0.
{{main|Self-complementary graph}}
A [[self-complementary graph]] is a graph that is [[graph isomorphism|isomorphic]] to its own complement.<ref name="bm"/> Examples include the four-vertex [[path graph]] and five-vertex [[cycle graph]]. There is no known characterization of self-complementary graphs.
Several classes of graphs are self-complementary, in the sense that the complement of any graph in one of these classes is another graph in the same class.
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| issue = 3
| pages = 253–267
| doi = 10.1016/0012-365X(72)90006-4| doi-access = free
}}.</ref> *[[Cograph]]s are defined as the graphs that can be built up from single vertices by [[disjoint union]] and complementation operations. They form a self-complementary family of graphs: the complement of any cograph is another different cograph. For cographs of more than one vertex, exactly one graph in each complementary pair is connected, and one equivalent definition of cographs is that each of their connected [[induced subgraph]]s has a disconnected complement. Another, self-complementary definition is that they are the graphs with no induced subgraph in the form of a four-vertex path.<ref>{{Citation | last1=Corneil | first1=D. G. | author1-link = Derek Corneil | last2=Lerchs | first2=H. | last3=Stewart Burlingham | first3=L. | title=Complement reducible graphs | doi=10.1016/0166-218X(81)90013-5 | mr=0619603 | year=1981 | journal=[[Discrete Applied Mathematics]] | volume=3 | pages=163–174 | issue=3| doi-access=free }}.</ref>
*Another self-complementary class of graphs is the class of [[split graph]]s, the graphs in which the vertices can be partitioned into a clique and an independent set. The same partition gives an independent set and a clique in the complement graph.<ref>{{citation
| last = Golumbic | first = Martin Charles | authorlink = Martin Charles Golumbic
Line 86 ⟶ 77:
| isbn = 0-12-289260-7
| mr = 0562306}}.</ref>
*The [[threshold graph]]s are the graphs formed by repeatedly adding either an independent vertex (one with no neighbors) or a [[universal vertex]] (adjacent to all previously-added vertices). These two operations are complementary and they generate a self-complementary class of graphs.<ref>{{citation
| last1 = Golumbic | first1 = Martin Charles
| last2 = Jamison | first2 = Robert E.
Line 97 ⟶ 88:
| volume = 52
| year = 2006}}.</ref>
==Algorithmic aspects==
In the [[analysis of algorithms]] on graphs, the distinction between a graph and its complement is an important one, because a [[sparse graph]] (one with a small number of edges compared to the number of pairs of vertices) will in general not have a sparse complement, and so an algorithm that takes time proportional to the number of edges on a given graph may take a much larger amount of time if the same algorithm is run on an explicit representation of the complement graph. Therefore, researchers have studied algorithms that perform standard graph computations on the complement of an input graph, using an [[implicit graph]] representation that does not require the explicit construction of the complement graph. In particular, it is possible to simulate either [[depth-first search]] or [[breadth-first search]] on the complement graph, in an amount of time that is linear in the size of the given graph, even when the complement graph may have a much larger size.<ref name="iy98"/> It is also possible to use these simulations to compute other properties concerning the connectivity of the complement graph.<ref name="iy98">{{citation
▲ | issue = 4
| journal = [[Information Processing Letters]]
| title = Linear time algorithms for graph search and connectivity determination on complement graphs
| year = 1998}}.</ref><ref>{{citation
| last1 = Kao | first1 = Ming-Yang
| last2 = Occhiogrosso | first2 = Neill
| last3 = Teng | first3 = Shang-Hua | author3-link = Shang-Hua Teng
| doi = 10.1023/A:1009720402326
| issue = 4
| journal = Journal of Combinatorial Optimization
| mr = 1669307
| pages = 351–359
| title = Simple and efficient graph compression schemes for dense and complement graphs
| volume = 2
| year = 1999}}.</ref>
==References==
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