Graphic matroid

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In the mathematical theory of matroids, a graphic matroid (also called a cycle matroid or polygon 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. [1] A matroid that is both graphic and co-graphic is sometimes called a planar matroid (but this should not be confused with matroids of rank 3, which generalize planar point configurations); these are exactly the graphic matroids formed from planar graphs.

Contents

Definition

A matroid may be defined as a family of finite sets (called the "independent sets" of the matroid) that is closed under subsets and that satisfies the "exchange property": if sets and are both independent, and is larger than , then there is an element such that remains independent. If is an undirected graph, and is the family of sets of edges that form forests in , then is clearly closed under subsets (removing edges from a forest leaves another forest). It also satisfies the exchange property: if and are both forests, and has more edges than , then it has fewer connected components, so by the pigeonhole principle there is a component of that contains vertices from two or more components of . Along any path in from a vertex in one component of to a vertex of another component, there must be an edge with endpoints in two components, and this edge may be added to to produce a forest with more edges. Thus, forms the independent sets of a matroid, called the graphic matroid of or . More generally, a matroid is called graphic whenever it is isomorphic to the graphic matroid of a graph, regardless of whether its elements are themselves edges in a graph. [2]

The bases of a graphic matroid are the full spanning forests of , and the circuits of are the simple cycles of . The rank in of a set of edges of a graph is where is the number of vertices in the subgraph formed by the edges in and is the number of connected components of the same subgraph. [2] The corank of the graphic matroid is known as the circuit rank or cyclomatic number.

The lattice of flats

The closure of a set of edges in is a flat consisting of the edges that are not independent of (that is, the edges whose endpoints are connected to each other by a path in ). This flat may be identified with the partition of the vertices of into the connected components of the subgraph formed by : Every set of edges having the same closure as gives rise to the same partition of the vertices, and may be recovered from the partition of the vertices, as it consists of the edges whose endpoints both belong to the same set in the partition. In the lattice of flats of this matroid, there is an order relation whenever the partition corresponding to flat  is a refinement of the partition corresponding to flat .

In this aspect of graphic matroids, the graphic matroid for a complete graph is particularly important, because it allows every possible partition of the vertex set to be formed as the set of connected components of some subgraph. Thus, the lattice of flats of the graphic matroid of is naturally isomorphic to the lattice of partitions of an -element set. Since the lattices of flats of matroids are exactly the geometric lattices, this implies that the lattice of partitions is also geometric. [3]

Representation

The graphic matroid of a graph can be defined as the column matroid of any oriented incidence matrix of . Such a matrix has one row for each vertex, and one column for each edge. The column for edge has in the row for one endpoint, in the row for the other endpoint, and elsewhere; the choice of which endpoint to give which sign is arbitrary. The column matroid of this matrix has as its independent sets the linearly independent subsets of columns.

If a set of edges contains a cycle, then the corresponding columns (multiplied by if necessary to reorient the edges consistently around the cycle) sum to zero, and is not independent. Conversely, if a set of edges forms a forest, then by repeatedly removing leaves from this forest it can be shown by induction that the corresponding set of columns is independent. Therefore, the column matrix is isomorphic to .

This method of representing graphic matroids works regardless of the field over which the incidence is defined. Therefore, graphic matroids form a subset of the regular matroids, matroids that have representations over all possible fields. [2]

The lattice of flats of a graphic matroid can also be realized as the lattice of a hyperplane arrangement, in fact as a subset of the braid arrangement, whose hyperplanes are the diagonals . Namely, if the vertices of are we include the hyperplane whenever is an edge of .

Matroid connectivity

A matroid is said to be connected if it is not the direct sum of two smaller matroids; that is, it is connected if and only if there do not exist two disjoint subsets of elements such that the rank function of the matroid equals the sum of the ranks in these separate subsets. Graphic matroids are connected if and only if the underlying graph is both connected and 2-vertex-connected. [2]

Minors and duality

Two different graphs (red) that are duals of the same planar graph (pale blue). Despite being non-isomorphic as graphs, they have isomorphic graphic matroids. Nonisomorphic planar duals.svg
Two different graphs (red) that are duals of the same planar graph (pale blue). Despite being non-isomorphic as graphs, they have isomorphic graphic matroids.

A matroid is graphic if and only if its minors do not include any of five forbidden minors: the uniform matroid , the Fano plane or its dual, or the duals of and defined from the complete graph and the complete bipartite graph . [2] [4] [5] The first three of these are the forbidden minors for the regular matroids, [6] and the duals of and are regular but not graphic.

If a matroid is graphic, its dual (a "co-graphic matroid") cannot contain the duals of these five forbidden minors. Thus, the dual must also be regular, and cannot contain as minors the two graphic matroids and . [2]

Because of this characterization and Wagner's theorem characterizing the planar graphs as the graphs with no or graph minor, it follows that a graphic matroid is co-graphic if and only if is planar; this is Whitney's planarity criterion. If is planar, the dual of is the graphic matroid of the dual graph of . While may have multiple dual graphs, their graphic matroids are all isomorphic. [2]

Algorithms

A minimum weight basis of a graphic matroid is a minimum spanning tree (or minimum spanning forest, if the underlying graph is disconnected). Algorithms for computing minimum spanning trees have been intensively studied; it is known how to solve the problem in linear randomized expected time in a comparison model of computation, [7] or in linear time in a model of computation in which the edge weights are small integers and bitwise operations are allowed on their binary representations. [8] The fastest known time bound that has been proven for a deterministic algorithm is slightly superlinear. [9]

Several authors have investigated algorithms for testing whether a given matroid is graphic. [10] [11] [12] For instance, an algorithm of Tutte (1960) solves this problem when the input is known to be a binary matroid. Seymour (1981) solves this problem for arbitrary matroids given access to the matroid only through an independence oracle, a subroutine that determines whether or not a given set is independent.

Some classes of matroid have been defined from well-known families of graphs, by phrasing a characterization of these graphs in terms that make sense more generally for matroids. These include the bipartite matroids, in which every circuit is even, and the Eulerian matroids, which can be partitioned into disjoint circuits. A graphic matroid is bipartite if and only if it comes from a bipartite graph and a graphic matroid is Eulerian if and only if it comes from an Eulerian graph. Within the graphic matroids (and more generally within the binary matroids) these two classes are dual: a graphic matroid is bipartite if and only if its dual matroid is Eulerian, and a graphic matroid is Eulerian if and only if its dual matroid is bipartite. [13]

Graphic matroids are one-dimensional rigidity matroids, matroids describing the degrees of freedom of structures of rigid beams that can rotate freely at the vertices where they meet. In one dimension, such a structure has a number of degrees of freedom equal to its number of connected components (the number of vertices minus the matroid rank) and in higher dimensions the number of degrees of freedom of a d-dimensional structure with n vertices is dn minus the matroid rank. In two-dimensional rigidity matroids, the Laman graphs play the role that spanning trees play in graphic matroids, but the structure of rigidity matroids in dimensions greater than two is not well understood. [14]

Related Research Articles

In graph theory, the girth of an undirected graph is the length of a shortest cycle contained in the graph. If the graph does not contain any cycles, its girth is defined to be infinity. For example, a 4-cycle (square) has girth 4. A grid has girth 4 as well, and a triangular mesh has girth 3. A graph with girth four or more is triangle-free.

In combinatorics, a branch of mathematics, a matroid is a structure that abstracts and generalizes the notion of linear independence in vector spaces. There are many equivalent ways to define a matroid axiomatically, the most significant being in terms of: independent sets; bases or circuits; rank functions; closure operators; and closed sets or flats. In the language of partially ordered sets, a finite simple matroid is equivalent to a geometric lattice.

<span class="mw-page-title-main">Bipartite graph</span> Graph divided into two independent sets

In the mathematical field of graph theory, a bipartite graph is a graph whose vertices can be divided into two disjoint and independent sets and , that is, every edge connects a vertex in to one in . Vertex sets and are usually called the parts of the graph. Equivalently, a bipartite graph is a graph that does not contain any odd-length cycles.

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">Eulerian path</span> Trail in a graph that visits each edge once

In graph theory, an Eulerian trail is a trail in a finite graph that visits every edge exactly once. Similarly, an Eulerian circuit or Eulerian cycle is an Eulerian trail that starts and ends on the same vertex. They were first discussed by Leonhard Euler while solving the famous Seven Bridges of Königsberg problem in 1736. The problem can be stated mathematically like this:

<span class="mw-page-title-main">Spanning tree</span> Tree which includes all vertices of a graph

In the mathematical field of graph theory, a spanning treeT of an undirected graph G is a subgraph that is a tree which includes all of the vertices of G. In general, a graph may have several spanning trees, but a graph that is not connected will not contain a spanning tree. If all of the edges of G are also edges of a spanning tree T of G, then G is a tree and is identical to T.

<span class="mw-page-title-main">Edge coloring</span> Problem of coloring a graphs edges such that meeting edges do not match

In graph theory, a proper edge coloring of a graph is an assignment of "colors" to the edges of the graph so that no two incident edges have the same color. For example, the figure to the right shows an edge coloring of a graph by the colors red, blue, and green. Edge colorings are one of several different types of graph coloring. The edge-coloring problem asks whether it is possible to color the edges of a given graph using at most k different colors, for a given value of k, or with the fewest possible colors. The minimum required number of colors for the edges of a given graph is called the chromatic index of the graph. For example, the edges of the graph in the illustration can be colored by three colors but cannot be colored by two colors, so the graph shown has chromatic index three.

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.

<span class="mw-page-title-main">Tutte polynomial</span> Algebraic encoding of graph connectivity

The Tutte polynomial, also called the dichromate or the Tutte–Whitney polynomial, is a graph polynomial. It is a polynomial in two variables which plays an important role in graph theory. It is defined for every undirected graph and contains information about how the graph is connected. It is denoted by .

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">Peripheral cycle</span> Graph cycle which does not separate remaining elements

In graph theory, a peripheral cycle in an undirected graph is, intuitively, a cycle that does not separate any part of the graph from any other part. Peripheral cycles 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.

<span class="mw-page-title-main">Pseudoforest</span> Graph with 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.

In matroid theory, the dual of a matroid is another matroid that has the same elements as , and in which a set is independent if and only if has a basis set disjoint from it.

In matroid theory, a field within mathematics, a gammoid is a certain kind of matroid, describing sets of vertices that can be reached by vertex-disjoint paths in a directed graph.

In mathematics, a partition matroid or partitional matroid is a matroid that is a direct sum of uniform matroids. It is defined over a base set in which the elements are partitioned into different categories. For each category, there is a capacity constraint - a maximum number of allowed elements from this category. The independent sets of a partition matroid are exactly the sets in which, for each category, the number of elements from this category is at most the category capacity.

In matroid theory, a binary matroid is a matroid that can be represented over the finite field GF(2). That is, up to isomorphism, they are the matroids whose elements are the columns of a (0,1)-matrix and whose sets of elements are independent if and only if the corresponding columns are linearly independent in GF(2).

In matroid theory, an Eulerian matroid is a matroid whose elements can be partitioned into a collection of disjoint circuits.

In mathematics, a bipartite matroid is a matroid all of whose circuits have even size.

<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 (1965) uses a reversed terminology, in which he called bond matroids "graphic" and cycle matroids "co-graphic", but this has not been followed by later authors.
  2. 1 2 3 4 5 6 7 Tutte, W. T. (1965), "Lectures on matroids" (PDF), Journal of Research of the National Bureau of Standards, 69B: 1–47, doi: 10.6028/jres.069b.001 , MR   0179781 . See in particular section 2.5, "Bond-matroid of a graph", pp. 5–6, section 5.6, "Graphic and co-graphic matroids", pp. 19–20, and section 9, "Graphic matroids", pp. 38–47.
  3. Birkhoff, Garrett (1995), Lattice Theory, Colloquium Publications, vol. 25 (3rd ed.), American Mathematical Society, p. 95, ISBN   9780821810255 .
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