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Matroid

Abstraction of linear independence of vectors

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Through Combinatorics, Linear algebra and Geometry

Matroid theory borrows extensively from the terms used in both linear algebra and graph theory, largely because it is the abstraction of various notions of central importance in these fields. Matroids have found applications in geometry, topology, combinatorial optimization, network theory, and coding theory.

Definition

There are many equivalent ways to define a (finite) matroid.

Independent sets

In terms of independence, a finite matroid M is a pair (E,I), where E is a finite set (called the ground set) and I is a family of subsets of E (called the independent sets) with the following properties:

  • (I1) The empty set is independent, i.e., ∅∈I.
  • (I2) Every subset of an independent set is independent, i.e., for each A′⊆A, if A∈I then A′∈I. This is sometimes called the hereditary property, or the downward-closed property.
  • (I3) If A and B are two independent sets (i.e., each set is independent) and A has more elements than B, then there exists x∈A∖B such that B∪{x} is independent. This is sometimes called the augmentation property or the independent set exchange property (cf. Steinitz exchange lemma)

The first two properties define a combinatorial structure known as an independence system (or abstract simplicial complex). Actually, assuming (I2), property (I1) is equivalent to the fact that at least one subset of E is independent, i.e., I≠∅.

Bases and circuits

A subset of the ground set E that is not independent is called dependent.

A maximal independent set – that is, an independent set that becomes dependent upon adding any element of E – is called a basis for the matroid.

A circuit in a matroid M is a minimal dependent subset of E – that is, a dependent set whose proper subsets are all independent. The term arises because the circuits of graphic matroids are cycles in the corresponding graphs.

The dependent sets, the bases, or the circuits of a matroid characterize the matroid completely: a set is independent if and only if it is not dependent, if and only if it is a subset of a basis, and if and only if it does not contain a circuit. The collections of dependent sets, of bases, and of circuits each have simple properties that may be taken as axioms for a matroid. For instance, one may define a matroid M to be a pair (E,B), where E is a finite set as before and B is a collection of subsets of E, called bases, with the following properties:

  • (B1) B is nonempty.
  • (B2) If A and B are distinct members of B and a∈A∖B, then there exists an element b∈B∖A such that (A∖{a})∪{b}∈B.

This property (B2) is called the basis exchange property. It follows from this property that no member of B can be a proper subset of any other.

Rank functions

It is a basic result of matroid theory, directly analogous to a similar theorem of bases in linear algebra, that any two bases of a matroid M have the same number of elements. This number is called the rank of M. If M is a matroid on E, and A is a subset of E, then a matroid on A can be defined by considering a subset of A to be independent if and only if it is independent in M. This allows us to talk about submatroids and about the rank of any subset of E. The rank of a subset A is given by the rank function r(A) of the matroid, which has the following properties:

  • (R1) The value of the rank function is always a non-negative integer.
  • (R2) For any subset A⊂E, we have r(A)≤|A|.
  • (R3) For any two subsets A,B⊂E, we have: r(A∪B)+r(A∩B)≤r(A)+r(B). That is, the rank is a submodular function.
  • (R4) For any set A and element x, we have: r(A)≤r(A∪{x})≤r(A)+1. From the first inequality it follows more generally that, if A⊆B⊆E, then r(A)≤r(B)≤r(E). That is, rank is a monotonic function.

These properties can be used as one of the alternative definitions of a finite matroid: If (E,r) satisfies these properties, then the independent sets of a matroid over E can be defined as those subsets A of E with r(A)=|A|. In the language of partially ordered sets, such a matroid structure is equivalent to the geometric lattice whose elements are the subsets A⊂M, partially ordered by inclusion.

The difference |A|−r(A) is called the nullity of the subset A. It is the minimum number of elements that must be removed from A to obtain an independent set. The nullity of E in M is called the nullity of M. The difference r(E)−r(A) is sometimes called the corank of the subset A.

Closure operators

Let M be a matroid on a finite set E, with rank function r as above. The closure or span cl⁡(A) of a subset A of E is the set

cl⁡(A)={x∈E∣r(A)=r(A∪{x})}.

This defines a closure operator cl:P(E)↦P(E) where P denotes the power set, with the following properties:

  • (C1) For all subsets X of E, X⊆cl⁡(X).
  • (C2) For all subsets X of E, cl⁡(X)=cl⁡(cl⁡(X)).
  • (C3) For all subsets X and Y of E with X⊆Y, cl⁡(X)⊆cl⁡(Y).
  • (C4) For all elements a and b from E and all subsets Y of E, if a∈cl⁡(Y∪{b})∖cl⁡(Y) then b∈cl⁡(Y∪{a})∖cl⁡(Y).

The first three of these properties are the defining properties of a closure operator. The fourth is sometimes called the Mac Lane–Steinitz exchange property. These properties may be taken as another definition of matroid: every function cl:P(E)→P(E) that obeys these properties determines a matroid.

Flats

A set whose closure equals itself is said to be closed, or a flat or subspace of the matroid. A set is closed if it is maximal for its rank, meaning that the addition of any other element to the set would increase the rank. The closed sets of a matroid are characterized by a covering partition property:

  • (F1) The whole point set E is closed.
  • (F2) If S and T are flats, then S∩T is a flat.
  • (F3) If S is a flat, then each element of E∖S is in precisely one of the flats T that cover S (meaning that T properly contains S, but there is no flat U between S and T).

The class L(M) of all flats, partially ordered by set inclusion, forms a matroid lattice. Conversely, every matroid lattice L forms a matroid over its set E of atoms under the following closure operator: for a set S of atoms with join ⋁S,

cl⁡(S)={x∈E∣x≤⋁S}.

The flats of this matroid correspond one-for-one with the elements of the lattice; the flat corresponding to lattice element y is the set

{x∈E∣x≤y}.

Thus, the lattice of flats of this matroid is naturally isomorphic to L.

Hyperplanes (coatoms)

In a matroid of rank r, a flat of rank r−1 is called a hyperplane, or co-atoms or copoints. These are the maximal proper flats; that is, the only superset of a hyperplane that is also a flat is the set E of all the elements of the matroid. An equivalent definition is that a coatom is a subset of E that does not span M, but such that adding any other element to it does make a spanning set.

The family H of hyperplanes of a matroid has the following properties, which may be taken as yet another axiomatization of matroids:

  • (H1) The ground set E itself is not a hyperplane.
  • (H2) There do not exist distinct sets X and Y in H with X⊆Y. That is, the hyperplanes form a Sperner family.
  • (H3) For every x∈E and distinct Y,Z∈H with x∉Y∪Z, there exists X∈H with (Y∩Z)∪{x}⊆X.

Graphoids

Minty (1966) defined a graphoid as a triple (L,C,D) in which C and D are classes of nonempty subsets of L such that

  • (G1) no element of C (called a "circuit") contains another,
  • (G2) no element of D (called a "cocircuit") contains another,
  • (G3) no set in C and set in D intersect in exactly one element, and
  • (G4) whenever L is represented as the disjoint union of subsets R,G,B with G={g} (a singleton set), then either an X∈C exists such that g∈X⊆R∪G or a Y∈D exists such that g∈Y⊆B∪G.

He proved that there is a matroid for which C is the class of circuits and D is the class of cocircuits. Conversely, if C and D are the circuit and cocircuit classes of a matroid M with ground set E, then (E,C,D) is a graphoid. Thus, graphoids give a self-dual cryptomorphic axiomatization of matroids.

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