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A matroid basis is a matroid independent set that is a maximal element under inclusion of subsets: no additional element of the ground set can be admitted. Maximum cardinality means having the largest size among all matroid independent sets. Maximality tests whether this particular selection can grow; maximum size compares it with every selection. In a matroid the two conditions coincide, so all matroid bases have a common size. They need not have equal weight. ^[ref]

Proof outline. If a maximal matroid independent set $B$ were smaller than another matroid independent set $J$, the matroid independence axioms would admit an element of $J\setminus B$, contradicting maximality. Finiteness allows every matroid independent set to grow to a matroid basis by successive admissible additions. In a general independence system, maximal selections can have different sizes, as in the hereditary nonmatroid greedy obstruction.

On the ground set $E=\{x,y,z\}$, permit exactlyThis lists every admissible subset; the excluded subsets are $\{x,y\}$, $\{x,z\}$, and $\{x,y,z\}$. It is an independence system: deleting elements from $\{y,z\}$ produces its listed singletons or the empty set, and deleting from a singleton produces the empty set. But $I=\{x\}$ and $J=\{y,z\}$ violate exchange: neither $y$ nor $z$ can be added to $I$. Thus it is not a matroid.

The descending-weight greedy algorithm admits $x$ first, then rejects both $y$ and $z$, returning $\{x\}$ with weight $10$. Exchanging the tied order of $y,z$ changes nothing. The admissible pair $\{y,z\}$ weighs $12$, exceeding every singleton and the empty set, so it is the true optimum. Both $\{x\}$ and $\{y,z\}$ are maximal elements under inclusion of subsets, but only the pair has maximum cardinality. This identifies exactly where the matroid greedy algorithm loses its guarantee: heredity preserves admissibility under deletions, while exchange prevents a locally maximal selection from being too small.

An independence system consists of a finite set $E$ and a nonempty family $\mathcal{I}$ of subsets such that $I\in \mathcal{I}$ and $J\subseteq I$ imply $J\in \mathcal{I}$. This is the hereditary condition: deleting chosen elements keeps a selection admissible. In particular, the empty set belongs to $\mathcal{I}$. An independence system becomes a matroid when it also satisfies the matroid independence axioms for exchange. The hereditary nonmatroid greedy obstruction shows why deletion alone does not justify a greedy algorithm.

A matroid independent set is a subset belonging to the family $\mathcal{I}$. Independence refers to the chosen matroid: for a linear matroid it means linear independence, and for a graphic matroid it means that the chosen edges contain no graph cycle. It is different from an independent set, which selects vertices with no edge between them.

A matroid is an independence system in which a smaller admissible selection can always grow using an element of a larger admissible selection. This exchange rule abstracts linear independence of vectors and the selection of edges forming a forest. It forces all matroid bases to have the same cardinality and makes the matroid greedy algorithm correct for maximizing their total weight. The useful surprise is that local choices become globally optimal because of a structural rule about admissible subsets, rather than a special numerical coincidence.

The weighted three-vector matroid below lets us inspect every subset and every possible size comparison. Its three vectors give three two-element matroid bases, yet their total weights differ. The graphic matroid of a graph triangle has exactly the same admissible labels. A pregeometry is a finitary closure-theoretic extension to possibly infinite sets.

For a finite matroid $M=(E,\mathcal{I})$, the convex hull of the indicator vectors of its matroid independent sets is exactly the displayed system, where $x(A)={\sum }_{e\in A}{x}_e$. It is an integral polytope. The equality $x(E)=r_M(E)$ instead gives the face corresponding to matroid bases; independence does not require that equality.

Proof. If $I$ is independent, $|I\cap A|\le r_M(A)$, so every independent indicator and every convex combination of them satisfies the inequalities. For the reverse inclusion, take an arbitrary real objective $c$. List its positive coordinates in nonincreasing order as $c_1\ge \cdots \ge c_k>0$, put $c_{k+1}=0$ and let $S_i$ be the first $i$ elements in this ordering. Run the matroid greedy algorithm on these elements, obtaining an independent set $I$. At every prefix the selected elements are maximal in $S_i$: an earlier rejected element cannot become admissible after further additions, by heredity. The augmentation axiom implies that every maximal independent set in $S_i$ has size $r_M(S_i)$. Hence $|I\cap S_i|=r_M(S_i)$.

For every point satisfying the displayed system, nonnegativity and telescoping giveThus every linear objective is maximized by an independent indicator, with the empty set used if all coefficients are nonpositive. Singleton rank inequalities bound every coordinate between zero and one, making the system compact. If it contained a point outside the compact convex hull of independent indicators, the finite-dimensional separating hyperplane theorem would supply an objective strictly larger at that point than at every independent indicator, a contradiction. This proves equality and integrality without assuming the desired convex-hull description in advance. Negative objective coefficients are discarded explicitly; maximizing over independent sets differs from maximizing over bases when such coefficients occur.

A matroid isomorphism between $(E,\mathcal{I})$ and $(E^{\prime },{\mathcal{I}}^{\prime })$ is a bijection $\varphi$ such that $I\in \mathcal{I}$ if and only if $\varphi (I)\in {\mathcal{I}}^{\prime }$. It relabels the ground set without changing independence. The number of labelled matroids therefore differs from the number of types up to matroid isomorphism.

A matroid is a pair $(X,\mathcal{I})$, where $X$ is a finite ground set and $\mathcal{I}\subseteq 2^X$ is its collection of matroid independent sets, satisfying the matroid independence axioms:

The last axiom is augmentation. In particular, every maximal matroid independent set within a given subset has maximum cardinality there: otherwise augmentation would enlarge it.

On fixed labelled ground sets of cardinality $1,2,3$, the numbers of matroids are respectively $2,5,16$.

For one element, the element is either a loop of a matroid or a nonloop, giving two choices. For two elements, rank of a matroid zero and two each give one possibility. At rank of a matroid one, the nonloops form any nonempty subset, giving $2^2-1=3$ more possibilities: total $1+3+1=5$.

For three elements, classify by the total rank of a matroid. At rank of a matroid zero every element is a matroid loop; at rank of a matroid three every subset is a matroid independent set. At rank of a matroid one, choose any nonempty subset of nonloops; exactly the empty set and their singletons are matroid independent sets. This gives seven possibilities.

At rank of a matroid two, either exactly two elements are nonloops, giving three choices for the remaining loop of a matroid, or all three are nonloops. In the latter case, pairs that are matroid dependent sets define parallel elements of a matroid. There can be no such pair, giving the uniform matroid $U_{2,3}$, or exactly one such pair, giving three choices. There cannot be exactly two such pairs: if $\{a,b\}$ and $\{a,c\}$ were matroid dependent sets but $\{b,c\}$ a matroid independent set, augmentation from $\{a\}$ to $\{b,c\}$ would fail. If all three pairs were matroid dependent sets, the rank of a matroid would be one. Hence rank of a matroid two gives $3+1+3=7$ examples.

Every listed possibility satisfies augmentation: the only nontrivial comparison on three elements is from a singleton to a two-element matroid independent set, and with at most one two-element matroid dependent set at least one addition works. The total is therefore $1+7+7+1=16$.

On a finite ground set $E$, a submodular rank function is a set function $r:2^E\to \mathbb{R}$ with the following properties:These are normalization, monotonicity, submodularity, and unit integer increments. In particular its values are nonnegative integers with $r(A)\le |A|$. Equivalently, one can require an integer-valued normalized monotone submodular function with $r(\{e\})\le 1$: diminishing returns then bounds every marginal increment by one. A general real-valued submodular function need not be a matroid rank.

The associated matroid isThus the graph's edges are the ground set, and the members of $\mathcal{I}$ are its matroid independent sets.

For the specified rank, if $(V,A)$ is a forest, $A$ itself is an allowed choice in the rank maximum, so $r(A)=|A|$. Conversely, if $r(A)=|A|$, some forest $F\subseteq A$ has $|F|=|A|$. Finiteness forces $F=A$, so $(V,A)$ is a forest. Hence the independent sets are exactly all forests in $G$, including the empty forest and forests with isolated vertices.

The matroid independence axioms can also be checked directly. The empty set is a forest, and deleting edges cannot create a cycle. For exchange, let forests $I,J$ have $|I|<|J|$. If every edge of $J$ joined vertices within one component of $(V,I)$, its restriction to each component $S$ would have at most $|S|-1$ edges. Summing would give $|J|\le |I|$, a contradiction. Thus some edge of $J\setminus I$ joins two components of $I$ and can be added without creating a cycle. This proves augmentation and identifies $M$ as the graphic matroid.

A pregeometry is a finitary closure structure with the exchange axiom, extending the closure description of a matroid to possibly infinite underlying sets. A pregeometry is a closure operator with finite character and exchange. Algebraic closure in a strongly minimal theory is a pregeometry.

On labelled ground sets of sizes $1,2,3$, there are respectively $2,5,16$ matroids, or $2,4,8$ up to matroid isomorphism. At rank of a matroid one, a nonempty subset of nonloops specifies all matroid independent sets of cardinality one. On three labels at rank of a matroid two, the three types are one matroid loop with an independent pair, no matroid loops with one pair of parallel elements of a matroid, and all pairs independent with the triple dependent.

On a finite ground set $E$, a submodular rank function is a normalised set function $r$ with $r(\varnothing )=0$, a monotone set function, and a submodular set function, such that $r(A\cup \{e\})-r(A)\in \{0,1\}$ for $e\notin A$. Equivalently, require nonnegative integer values, monotonicity, submodularity and $r(\{e\})\le 1$. The diminishing returns characterization of submodularity bounds each marginal by its singleton value. Thus $0\le r(A)\le |A|$.

These functions are precisely the rank functions of matroids. To see the converse direction, define $\mathcal{I}=\{A:r(A)=|A|\}$. It contains the empty set. If $B\subseteq A\in \mathcal{I}$, the unit marginal bounds give $|A|=r(A)\le r(B)+|A\setminus B|$, so $r(B)=|B|$ and heredity holds. For augmentation, suppose $A,B\in \mathcal{I}$ with $|A|<|B|$. If every $e\in B\setminus A$ had zero marginal over $A$, diminishing returns would keep each marginal zero as they are added successively. This would give $r(A\cup B)=r(A)=|A|<|B|=r(B)$, contradicting monotonicity. Some marginal is therefore one, giving an independent augmentation.

Finally any inclusion-maximal $I\subseteq A$ in this independence family has $r(I\cup \{e\})=r(I)$ for every remaining $e\in A\setminus I$. Successively adding them and using diminishing returns shows $r(A)=r(I)=|I|$, so the resulting matroid really has rank $r$. The forward direction is submodularity of matroid rank. These integer increment conditions distinguish matroid ranks from arbitrary real-valued submodular functions.

A mathematician whose work includes graph theory and matroids; Tutte's theorem on perfect matchings is one of his fundamental results.

University of St Andrews biography and portrait collection.