# Cycle (graph theory)

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A graph with edges colored to illustrate path H-A-B, closed path or walk with a repeated vertex B-D-E-F-D-C-B and a cycle with no repeated edge or vertex H-D-G-H

In graph theory, there are two different types of object called cycles; a closed walk and a simple cycle. A closed walk, consists of a sequence of vertices starting and ending at the same vertex, with each two consecutive vertices in the sequence adjacent to each other in the graph. A simple cycle, also called a circuit, circle, or polygon, is a closed walk with no repetitions of vertices and edges allowed, other than the repetition of the starting and ending vertex. Simple cycles may also be described by their sets of edges, unlike closed walks for which the multiset of edges does not unambiguously determine the vertex ordering. A directed cycle in a directed graph is a sequence of vertices starting and ending at the same vertex such that, for each two consecutive vertices of the cycle, there exists an edge directed from the earlier vertex to the later one; the same distinction between closed walks and simple cycles may be made in the directed case.[1]

## Chordless cycles

A chordless cycle in a graph, also called a hole or an induced cycle, is a cycle such that no two vertices of the cycle are connected by an edge that does not itself belong to the cycle. An antihole is the complement of a graph hole. Chordless cycles may be used to characterize perfect graphs: by the strong perfect graph theorem, a graph is perfect if and only if none of its holes or antiholes have an odd number of vertices that is greater than three. A chordal graph, a special type of perfect graph, has no holes of any size greater than three.

The girth of a graph is the length of its shortest cycle; this cycle is necessarily chordless. Cages are defined as the smallest regular graphs with given combinations of degree and girth.

A peripheral cycle is a cycle in a graph with the property that every two edges not on the cycle can be connected by a path whose interior vertices avoid the cycle. In a graph that is not formed by adding one edge to a cycle, a peripheral cycle must be an induced cycle.

## Cycle space

The term cycle may also refer to an element of the cycle space of a graph. This consists of the edge sets that have an even degree at every vertex; it forms a vector space over the two-element finite field. Using methods from algebraic topology, it may be generalized to vector spaces or modules over other rings such as the integers, real numbers, etc. By Veblen's theorem, every element of the cycle space may be formed by combining simple cycles; a cycle basis of the graph is a set of simple cycles that forms a basis of the cycle space.[2][3]

## Cycle detection

An undirected graph has a cycle if and only if a depth-first search (DFS) finds an edge that points to an already-visited vertex (a back edge).[4] Equivalently, all the back edges, which DFS skips over, are part of cycles.[5] In the case of undirected graphs, only O(n) time is required to find a cycle in an n-vertex graph, since at most n − 1 edges can be tree edges.

A directed graph has a cycle if and only if a DFS finds a back edge. Forward and cross edges do not necessarily indicate cycles. Many topological sorting algorithms will detect cycles too, since those are obstacles for topological order to exist. Also, if a directed graph has been divided into strongly connected components, cycles only exist within the components and not between them, since cycles are strongly connected.[5]

Applications of cycle detection include the use of wait-for graphs to detect deadlocks in concurrent systems.[6]

## Covering graphs by cycles

In his 1736 paper on the Seven Bridges of Königsberg, widely considered to be the birth of graph theory, Leonhard Euler proved that, for a finite undirected graph to have a closed walk that visits each edge exactly once, it is necessary and sufficient that it be connected and have even degree at each vertex. The corresponding characterization for the existence of a closed walk visiting each edge exactly once in a directed graph is that the graph be strongly connected and have equal numbers of incoming and outgoing edges at each vertex. In either case, the resulting walk is known as an Euler cycle or Euler tour. If a finite undirected graph has even degree at each of its vertices, regardless of whether it is connected, then it is possible to find a set of simple cycles that together cover each edge exactly once: this is Veblen's theorem. [7]When a connected graph does not meet the conditions of Euler's theorem, a closed walk of minimum length covering each edge at least once can nevertheless be found in polynomial time by solving the route inspection problem.

The problem of finding a single simple cycle that covers each vertex exactly once, rather than covering the edges, is much harder. Such a cycle is known as a Hamiltonian cycle, and determining whether it exists is NP-complete.[8] Much research has been published concerning classes of graphs that can be guaranteed to contain Hamiltonian cycles; one example is Ore's theorem that a Hamiltonian cycle can always be found in a graph for which every non-adjacent pair of vertices have degrees summing to at least the total number of vertices in the graph.[9]

The cycle double cover states that, for every bridgeless graph, there exists a multiset of simple cycles that covers each edge of the graph exactly twice. Proving that this is true (or finding a counterexample) remains an open problem.[10]

## Graph classes defined by cycles

Several important classes of graphs can be defined by or characterized by their cycles. These include:

## References

1. ^ Balakrishnan, V.K. (2005). Schaum's outline of theory and problems of graph theory ([Nachdr.]. ed.). McGraw-Hill. ISBN 978-0070054899.
2. ^ Gross, Jonathan L.; Yellen, Jay (2005), "4.6 Graphs and Vector Spaces", Graph Theory and Its Applications (2nd ed.), CRC Press, pp. 197–207, ISBN 9781584885054.
3. ^ Diestel, Reinhard (2012), "1.9 Some linear algebra", Graph Theory, Graduate Texts in Mathematics 173, Springer, pp. 23–28.
4. ^ Tucker, Alan (2006). "Chapter 2: Covering Circuits and Graph Colorings". Applied Combinatorics (5th ed.). Hoboken: John Wiley & sons. p. 49. ISBN 978-0-471-73507-6.
5. ^ a b Sedgewick, Robert (1983), "Graph algorithms", Algorithms, Addison-Wesley, ISBN 0-201-06672-6
6. ^ Silberschatz, Abraham; Peter Galvin; Greg Gagne (2003). Operating System Concepts. John Wiley & Sons, INC. p. 260. ISBN 0-471-25060-0.
7. ^ Veblen, Oswald (1912), "An Application of Modular Equations in Analysis Situs", Annals of Mathematics, Second Series 14 (1): 86–94, JSTOR 1967604.
8. ^ Richard M. Karp (1972), "Reducibility Among Combinatorial Problems", in R. E. Miller and J. W. Thatcher, Complexity of Computer Computations, New York: Plenum, pp. 85–103.
9. ^ Ore, Ø. (1960), "Note on Hamilton circuits", American Mathematical Monthly 67 (1): 55, JSTOR 2308928.
10. ^ Jaeger, F. (1985), "A survey of the cycle double cover conjecture", Annals of Discrete Mathematics 27 – Cycles in Graphs, North-Holland Mathematics Studies 27, pp. 1–12, doi:10.1016/S0304-0208(08)72993-1..