Peripheral cycle

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In this graph, the red triangle formed by vertices 1, 2, and 5 is a peripheral cycle: the four remaining edges form a single bridge. However, pentagon 1-2-3-4-5 is not peripheral, as the two remaining edges form two separate bridges. 6n-graf-clique.svg
In this graph, the red triangle formed by vertices 1, 2, and 5 is a peripheral cycle: the four remaining edges form a single bridge. However, pentagon 1–2–3–4–5 is not peripheral, as the two remaining edges form two separate bridges.

In graph theory, a peripheral cycle (or peripheral circuit) in an undirected graph is, intuitively, a cycle that does not separate any part of the graph from any other part. Peripheral cycles (or, as they were initially called, peripheral polygons, because Tutte called cycles "polygons") were first studied by Tutte (1963), and play important roles in the characterization of planar graphs and in generating the cycle spaces of nonplanar graphs. [1]

Contents

Definitions

A peripheral cycle in a graph can be defined formally in one of several equivalent ways:

The equivalence of these definitions is not hard to see: a connected subgraph of (together with the edges linking it to ), or a chord of a cycle that causes it to fail to be induced, must in either case be a bridge, and must also be an equivalence class of the binary relation on edges in which two edges are related if they are the ends of a path with no interior vertices in . [7]

Properties

Peripheral cycles appear in the theory of polyhedral graphs, that is, 3-vertex-connected planar graphs. For every planar graph , and every planar embedding of , the faces of the embedding that are induced cycles must be peripheral cycles. In a polyhedral graph, all faces are peripheral cycles, and every peripheral cycle is a face. [8] It follows from this fact that (up to combinatorial equivalence, the choice of the outer face, and the orientation of the plane) every polyhedral graph has a unique planar embedding. [9]

In planar graphs, the cycle space is generated by the faces, but in non-planar graphs peripheral cycles play a similar role: for every 3-vertex-connected finite graph, the cycle space is generated by the peripheral cycles. [10] The result can also be extended to locally-finite but infinite graphs. [11] In particular, it follows that 3-connected graphs are guaranteed to contain peripheral cycles. There exist 2-connected graphs that do not contain peripheral cycles (an example is the complete bipartite graph , for which every cycle has two bridges) but if a 2-connected graph has minimum degree three then it contains at least one peripheral cycle. [12]

Peripheral cycles in 3-connected graphs can be computed in linear time and have been used for designing planarity tests. [13] They were also extended to the more general notion of non-separating ear decompositions. In some algorithms for testing planarity of graphs, it is useful to find a cycle that is not peripheral, in order to partition the problem into smaller subproblems. In a biconnected graph of circuit rank less than three (such as a cycle graph or theta graph) every cycle is peripheral, but every biconnected graph with circuit rank three or more has a non-peripheral cycle, which may be found in linear time. [14]

Generalizing chordal graphs, Seymour & Weaver (1984) define a strangulated graph to be a graph in which every peripheral cycle is a triangle. They characterize these graphs as being the clique-sums of chordal graphs and maximal planar graphs. [15]

Peripheral cycles have also been called non-separating cycles, [2] but this term is ambiguous, as it has also been used for two related but distinct concepts: simple cycles the removal of which would disconnect the remaining graph, [16] and cycles of a topologically embedded graph such that cutting along the cycle would not disconnect the surface on which the graph is embedded. [17]

In matroids, a non-separating circuit is a circuit of the matroid (that is, a minimal dependent set) such that deleting the circuit leaves a smaller matroid that is connected (that is, that cannot be written as a direct sum of matroids). [18] These are analogous to peripheral cycles, but not the same even in graphic matroids (the matroids whose circuits are the simple cycles of a graph). For example, in the complete bipartite graph , every cycle is peripheral (it has only one bridge, a two-edge path) but the graphic matroid formed by this bridge is not connected, so no circuit of the graphic matroid of is non-separating.

Related Research Articles

In graph theory, a planar graph is a graph that can be embedded in the plane, i.e., it can be drawn on the plane in such a way that its edges intersect only at their endpoints. In other words, it can be drawn in such a way that no edges cross each other. Such a drawing is called a plane graph or planar embedding of the graph. A plane graph can be defined as a planar graph with a mapping from every node to a point on a plane, and from every edge to a plane curve on that plane, such that the extreme points of each curve are the points mapped from its end nodes, and all curves are disjoint except on their extreme points.

<span class="mw-page-title-main">Component (graph theory)</span> Maximal subgraph whose vertices can reach each other

In graph theory, a component of an undirected graph is a connected subgraph that is not part of any larger connected subgraph. The components of any graph partition its vertices into disjoint sets, and are the induced subgraphs of those sets. A graph that is itself connected has exactly one component, consisting of the whole graph. Components are sometimes called connected components.

In graph theory, a branch of mathematics, the (binary) cycle space of an undirected graph is the set of its even-degree subgraphs.

This is a glossary of graph theory. Graph theory is the study of graphs, systems of nodes or vertices connected in pairs by lines or edges.

<span class="mw-page-title-main">Snark (graph theory)</span> 3-regular graph with no 3-edge-coloring

In the mathematical field of graph theory, a snark is an undirected graph with exactly three edges per vertex whose edges cannot be colored with only three colors. In order to avoid trivial cases, snarks are often restricted to have additional requirements on their connectivity and on the length of their cycles. Infinitely many snarks exist.

<span class="mw-page-title-main">Chordal graph</span> Graph where all long cycles have a chord

In the mathematical area of graph theory, a chordal graph is one in which all cycles of four or more vertices have a chord, which is an edge that is not part of the cycle but connects two vertices of the cycle. Equivalently, every induced cycle in the graph should have exactly three vertices. The chordal graphs may also be characterized as the graphs that have perfect elimination orderings, as the graphs in which each minimal separator is a clique, and as the intersection graphs of subtrees of a tree. They are sometimes also called rigid circuit graphs or triangulated graphs: a chordal completion of a graph is typically called a triangulation of that graph.

In the mathematical theory of matroids, a graphic matroid is a matroid whose independent sets are the forests in a given finite undirected graph. The dual matroids of graphic matroids are called co-graphic matroids or bond matroids. A matroid that is both graphic and co-graphic is sometimes called a planar matroid ; these are exactly the graphic matroids formed from planar graphs.

<span class="mw-page-title-main">Circuit rank</span> Fewest graph edges whose removal breaks all cycles

In graph theory, a branch of mathematics, the circuit rank, cyclomatic number, cycle rank, or nullity of an undirected graph is the minimum number of edges that must be removed from the graph to break all its cycles, making it into a tree or forest. It is equal to the number of independent cycles in the graph. Unlike the corresponding feedback arc set problem for directed graphs, the circuit rank r is easily computed using the formula

The arboricity of an undirected graph is the minimum number of forests into which its edges can be partitioned. Equivalently it is the minimum number of spanning forests needed to cover all the edges of the graph. The Nash-Williams theorem provides necessary and sufficient conditions for when a graph is k-arboric.

<span class="mw-page-title-main">Dual graph</span> Graph representing faces of another graph

In the mathematical discipline of graph theory, the dual graph of a planar graph G is a graph that has a vertex for each face of G. The dual graph has an edge for each pair of faces in G that are separated from each other by an edge, and a self-loop when the same face appears on both sides of an edge. Thus, each edge e of G has a corresponding dual edge, whose endpoints are the dual vertices corresponding to the faces on either side of e. The definition of the dual depends on the choice of embedding of the graph G, so it is a property of plane graphs rather than planar graphs. For planar graphs generally, there may be multiple dual graphs, depending on the choice of planar embedding of the graph.

In graph theory, a connected graph is k-edge-connected if it remains connected whenever fewer than k edges are removed.

<span class="mw-page-title-main">Factor-critical graph</span> Graph of n vertices with a perfect matching for every subgraph of n-1 vertices

In graph theory, a mathematical discipline, a factor-critical graph is a graph with n vertices in which every induced subgraph of n − 1 vertices has a perfect matching.

<span class="mw-page-title-main">Cactus graph</span> Mathematical tree of cycles

In graph theory, a cactus is a connected graph in which any two simple cycles have at most one vertex in common. Equivalently, it is a connected graph in which every edge belongs to at most one simple cycle, or in which every block is an edge or a cycle.

<span class="mw-page-title-main">Pseudoforest</span> Graph with at most one cycle per component

In graph theory, a pseudoforest is an undirected graph in which every connected component has at most one cycle. That is, it is a system of vertices and edges connecting pairs of vertices, such that no two cycles of consecutive edges share any vertex with each other, nor can any two cycles be connected to each other by a path of consecutive edges. A pseudotree is a connected pseudoforest.

<span class="mw-page-title-main">Clique-sum</span> Gluing graphs at complete subgraphs

In graph theory, a branch of mathematics, a clique sum is a way of combining two graphs by gluing them together at a clique, analogous to the connected sum operation in topology. If two graphs G and H each contain cliques of equal size, the clique-sum of G and H is formed from their disjoint union by identifying pairs of vertices in these two cliques to form a single shared clique, and then deleting all the clique edges or possibly deleting some of the clique edges. A k-clique-sum is a clique-sum in which both cliques have exactly k vertices. One may also form clique-sums and k-clique-sums of more than two graphs, by repeated application of the clique-sum operation.

<span class="mw-page-title-main">Grinberg's theorem</span> On Hamiltonian cycles in planar graphs

In graph theory, Grinberg's theorem is a necessary condition for a planar graph to contain a Hamiltonian cycle, based on the lengths of its face cycles. If a graph does not meet this condition, it is not Hamiltonian. The result has been widely used to prove that certain planar graphs constructed to have additional properties are not Hamiltonian; for instance it can prove non-Hamiltonicity of some counterexamples to Tait's conjecture that cubic polyhedral graphs are Hamiltonian.

<span class="mw-page-title-main">Cycle basis</span> Cycles in a graph that generate all cycles

In graph theory, a branch of mathematics, a cycle basis of an undirected graph is a set of simple cycles that forms a basis of the cycle space of the graph. That is, it is a minimal set of cycles that allows every even-degree subgraph to be expressed as a symmetric difference of basis cycles.

<span class="mw-page-title-main">Ear decomposition</span> Partition of graph into sequence of paths

In graph theory, an ear of an undirected graph G is a path P where the two endpoints of the path may coincide, but where otherwise no repetition of edges or vertices is allowed, so every internal vertex of P has degree two in G. An ear decomposition of an undirected graph G is a partition of its set of edges into a sequence of ears, such that the one or two endpoints of each ear belong to earlier ears in the sequence and such that the internal vertices of each ear do not belong to any earlier ear. Additionally, in most cases the first ear in the sequence must be a cycle. An open ear decomposition or a proper ear decomposition is an ear decomposition in which the two endpoints of each ear after the first are distinct from each other.

In graph theory and graph drawing, a subhamiltonian graph is a subgraph of a planar Hamiltonian graph.

<span class="mw-page-title-main">Matroid parity problem</span> Largest independent set of paired elements

In combinatorial optimization, the matroid parity problem is a problem of finding the largest independent set of paired elements in a matroid. The problem was formulated by Lawler (1976) as a common generalization of graph matching and matroid intersection. It is also known as polymatroid matching, or the matchoid problem.

References

  1. Tutte, W. T. (1963), "How to draw a graph", Proceedings of the London Mathematical Society, Third Series, 13: 743–767, doi:10.1112/plms/s3-13.1.743, MR   0158387 .
  2. 1 2 Di Battista, Giuseppe; Eades, Peter; Tamassia, Roberto; Tollis, Ioannis G. (1998), Graph Drawing: Algorithms for the Visualization of Graphs, Prentice Hall, pp. 74–75, ISBN   978-0-13-301615-4 .
  3. Not to be confused with bridge (graph theory), a different concept.
  4. Tutte, W. T. (1960), "Convex representations of graphs", Proceedings of the London Mathematical Society, Third Series, 10: 304–320, doi:10.1112/plms/s3-10.1.304, MR   0114774 .
  5. This is the definition of peripheral cycles originally used by Tutte (1963). Seymour & Weaver (1984) use the same definition of a peripheral cycle, but with a different definition of a bridge that more closely resembles the induced-cycle definition for peripheral cycles.
  6. This is, essentially, the definition used by Bruhn (2004). However, Bruhn distinguishes the case that has isolated vertices from disconnections caused by the removal of .
  7. See e.g. Theorem 2.4 of Tutte (1960), showing that the vertex sets of bridges are path-connected, see Seymour & Weaver (1984) for a definition of bridges using chords and connected components, and also see Di Battista et al. (1998) for a definition of bridges using equivalence classes of the binary relation on edges.
  8. Tutte (1963), Theorems 2.7 and 2.8.
  9. See the remarks following Theorem 2.8 in Tutte (1963). As Tutte observes, this was already known to Whitney, Hassler (1932), "Non-separable and planar graphs", Transactions of the American Mathematical Society, 34 (2): 339–362, doi: 10.2307/1989545 , JSTOR   1989545, MR   1501641 .
  10. Tutte (1963), Theorem 2.5.
  11. Bruhn, Henning (2004), "The cycle space of a 3-connected locally finite graph is generated by its finite and infinite peripheral circuits", Journal of Combinatorial Theory, Series B, 92 (2): 235–256, doi: 10.1016/j.jctb.2004.03.005 , MR   2099143 .
  12. Thomassen, Carsten; Toft, Bjarne (1981), "Non-separating induced cycles in graphs", Journal of Combinatorial Theory, Series B, 31 (2): 199–224, doi: 10.1016/S0095-8956(81)80025-1 , MR   0630983 .
  13. Schmidt, Jens M. (2014), "The Mondshein Sequence", Proceedings of the 41st International Colloquium on Automata, Languages and Programming (ICALP'14), Lecture Notes in Computer Science, vol. 8572, pp. 967–978, doi:10.1007/978-3-662-43948-7_80, ISBN   978-3-662-43947-0 .
  14. Di Battista et al. (1998), Lemma 3.4, pp. 75–76.
  15. Seymour, P. D.; Weaver, R. W. (1984), "A generalization of chordal graphs", Journal of Graph Theory, 8 (2): 241–251, doi:10.1002/jgt.3190080206, MR   0742878 .
  16. E.g. see Borse, Y. M.; Waphare, B. N. (2008), "Vertex disjoint non-separating cycles in graphs", The Journal of the Indian Mathematical Society, New Series, 75 (1–4): 75–92 (2009), MR   2662989 .
  17. E.g. see Cabello, Sergio; Mohar, Bojan (2007), "Finding shortest non-separating and non-contractible cycles for topologically embedded graphs", Discrete and Computational Geometry , 37 (2): 213–235, doi: 10.1007/s00454-006-1292-5 , MR   2295054 .
  18. Maia, Bráulio, Junior; Lemos, Manoel; Melo, Tereza R. B. (2007), "Non-separating circuits and cocircuits in matroids", Combinatorics, complexity, and chance, Oxford Lecture Ser. Math. Appl., vol. 34, Oxford: Oxford Univ. Press, pp. 162–171, doi:10.1093/acprof:oso/9780198571278.003.0010, ISBN   978-0-19-857127-8, MR   2314567 {{citation}}: CS1 maint: multiple names: authors list (link).