Matroid Matroid

Matroid - Definition and Overview

In combinatorial mathematics, a matroid is a structure that captures the essence of a notion of "independence" that generalizes linear independence in vector spaces. Formally, a matroid M on a finite set E is a pair (E, I), where I is a collection of subsets of E (called the independent sets) with the following properties:

  • the empty set is independent
  • every subset of an independent set is independent
  • if A and B are two independent sets and A has more elements than B, then there exists an element in A which is not in B and when added to B still gives an independent set
Contents

Examples

  • If E is any finite subset of a vector space V, then we can define a matroid M on E by taking the linearly independent elements in E to be the independent sets of M.
  • Every finite simple graph G gives rise to a matroid as follows: take as E the set of all edges in G and consider a set of edges independent iff it is not possible to form a simple cycle with them. This is called the "forest matroid"
  • Let E be a finite set and k a natural number. The subsets of E with at most k elements are the independent sets of a matroid on E.

Further definitions and properties

A subset of E is called dependent if it is not independent. A dependent set all of whose proper subsets are independent is called a circuit (with the terminology coming from the graph example above). An independent set all of whose proper supersets are dependent is called a basis (with the terminology coming from the vector space example above). Hence bases are independent sets which cannot increase further while being indepedent (maximal independent sets), and circuits are dependent sets which cannot decrease and still being dependent (minimal dependent sets). An important fact is that all bases of a matroid have the same number of elements, called the rank of M. In general, the circuits of M have different sizes.

In the first example matroid above, a basis is a basis in the sense of linear algebra of the subspace spanned by E, and a circuit is a minimal set of dependent vectors of E. In the second example, a basis is the same as a spanning forest of the graph G, and circuits are cycles in the graph. In the third example, a basis is any subset of E with k elements, and a circuit is any subset of k + 1 elements.

If A is a subset of E, then a matroid on A can be defined by considering a subset of A independent if and only if it is independent in M. This allows to talk about the rank of any subset of E.

The rank function r assigns a natural number to every subset of E and has the following properties:

  1. r(A) ≤ |A| for all subsets A of E
  2. if A and B are subsets of E with AB, then r(A) ≤ r(B)
  3. for any two subsets A and B of E, we have r(AB) + r(AB) ≤ r(A) + r(B)

In fact, these three properties can be used as an alternative definition of matroids: the independent sets are then defined as those subsets A of E with r(A) = |A|.

If M is a matroid, we can define the dual matroid M* by taking the same underlying set and calling a set independent in M* if and only if it is contained in the complement of some basis of M. One checks easily that M* is indeed a matroid.

History

The matroid concept was introduced by Hassler Whitney in 1935 in his paper "On the abstract properties of linear dependence".

See also

Links and references

  • Steven R. Pagano: Matroids and Signed Graphs (http://www.ms.uky.edu/~pagano/Matridx.htm)
  • Oxley, James G.: "Matroid Theory", Oxford University Press, New York, 1992
  • PlanetMath article on matroids (http://planetmath.org/encyclopedia/Matroid.html). Contains several other equivalent definitions of matroids.
  • Sandra Kingan: Matroid theory (http://members.aol.com/matroids/). Lots of links.

Example Usage of Matroid

babocherub: @sioum Matroid 강의에 강의 노트 나누어 주시지요? 저는 수강신청을 할 수는 없지만 수강하고 싶은데 제 강의 노트도 부탁드립니다.=)
sioum: 내년 봄에 MAS480 수학특강과목으로 Matroid theory를 강의할 예정인데 어제 실라버스를 올렸습니다 이 내용은 첫 강의라 다음 봄은 바쁠 것 같습니다 http://bit.ly/5q3mnN
yomcat: "this Matroid is paving. Now go look up the properties in Oxley". That's a boring proof.
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