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mathematics Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics ...
, Hall's marriage theorem, proved by , is a theorem with two equivalent formulations: * The
combinatorial Combinatorics is an area of mathematics primarily concerned with counting, both as a means and an end in obtaining results, and certain properties of finite structures. It is closely related to many other areas of mathematics and has many ap ...
formulation deals with a collection of
finite Finite is the opposite of infinite. It may refer to: * Finite number (disambiguation) * Finite set, a set whose cardinality (number of elements) is some natural number * Finite verb, a verb form that has a subject, usually being inflected or marke ...
sets. It gives a necessary and sufficient condition for being able to select a distinct element from each set. * The graph theoretic formulation deals with a
bipartite graph In the mathematical field of graph theory, a bipartite graph (or bigraph) is a graph whose vertices can be divided into two disjoint and independent sets U and V, that is every edge connects a vertex in U to one in V. Vertex sets U and V are ...
. It gives a necessary and sufficient condition for finding a matching that covers at least one side of the graph.


Combinatorial formulation


Statement

Let \mathcal F be a
family Family (from la, familia) is a Social group, group of people related either by consanguinity (by recognized birth) or Affinity (law), affinity (by marriage or other relationship). The purpose of the family is to maintain the well-being of its ...
of
finite sets In mathematics, particularly set theory, a finite set is a set that has a finite number of elements. Informally, a finite set is a set which one could in principle count and finish counting. For example, :\ is a finite set with five elements. Th ...
. Here, \mathcal F is itself allowed to be infinite (although the sets in it are not) and to contain the same set multiple times. Let X be the union of all the sets in \mathcal F, the set of elements that belong to at least one of its sets. A transversal for F is a subset of X that can be obtained by choosing a distinct element from each set in \mathcal F. This concept can be formalized by defining a transversal to be the
image An image is a visual representation of something. It can be two-dimensional, three-dimensional, or somehow otherwise feed into the visual system to convey information. An image can be an artifact, such as a photograph or other two-dimensiona ...
of an
injective function In mathematics, an injective function (also known as injection, or one-to-one function) is a function that maps distinct elements of its domain to distinct elements; that is, implies . (Equivalently, implies in the equivalent contrapositiv ...
f:\mathcal F\to X such that f(S)\in S for each S\in\mathcal F. An alternative term for ''transversal'' is ''system of distinct representatives''. The collection \mathcal F satisfies the marriage condition when each subfamily of \mathcal F contains at least as many distinct members as its number of sets. That is, for all \mathcal G \subseteq \mathcal F, , \mathcal G, \le\Bigl, \bigcup_ S\Bigr, . If a transversal exists then the marriage condition must be true: the function f used to define the transversal maps \mathcal G to a subset of its union, of size equal to , \mathcal G, , so the whole union must be at least as large. Hall's theorem states that the converse is also true:


Examples

;Example 1 : Consider the family \mathcal F=\ with X=\ and \begin A_1&=\\\ A_2&=\\\ A_3&=\.\\ \end The transversal \ could be generated by the function that maps A_1 to 1, A_2 to 5, and A_3 to 3, or alternatively by the function that maps A_1 to 3, A_2 to 1, and A_3 to 5. There are other transversals, such as \ and \. Because this family has at least one transversal, the marriage condition is met. Every subfamily of \mathcal F has equal size to the set of representatives it is mapped to, which is less than or equal to the size of the union of the subfamily. ;Example 2 : Consider \mathcal F=\ with \begin A_1&=\\\ A_2&=\\\ A_3&=\\\ A_4&=\.\\ \end No valid transversal exists; the marriage condition is violated as is shown by the subfamily \mathcal G=\. Here the number of sets in the subfamily is , \mathcal G, =3, while the union of the three sets A_2\cup A_3\cup A_4=\ contains only two elements.


Graph theoretic formulation

Let G=(X,Y,E) be a finite
bipartite graph In the mathematical field of graph theory, a bipartite graph (or bigraph) is a graph whose vertices can be divided into two disjoint and independent sets U and V, that is every edge connects a vertex in U to one in V. Vertex sets U and V are ...
with bipartite sets X and Y and edge set E. An ''X-perfect matching'' (also called an ''X-saturating matching'') is a matching, a set of disjoint edges, which covers every vertex in X. For a subset W of X, let N_G(W) denote the
neighborhood A neighbourhood (British English, Irish English, Australian English and Canadian English) or neighborhood (American English; see spelling differences) is a geographically localised community within a larger city, town, suburb or rural area, ...
of W in G, the set of all vertices in Y that are adjacent to at least one element of W. The marriage theorem in this formulation states that there is an X-perfect matching
if and only if In logic and related fields such as mathematics and philosophy, "if and only if" (shortened as "iff") is a biconditional logical connective between statements, where either both statements are true or both are false. The connective is bicondi ...
for every subset W of X: , W, \leq , N_G(W), . In other words, every subset W of X must have sufficiently many neighbors in Y.


Proof of the graph theoretic version

;Easy direction : In an X-perfect matching M, every edge incident to W connects to a distinct neighbor of W in Y, so the number of these matched neighbors is at least , W, . The number of all neighbors of W is at least as large. ;Hard direction : The theorem can be proven if the assumption that there is no X-perfect matching leads to the conclusion that Hall's condition is violated for at least one W\subseteq X. Let M be a maximum matching, and let u be any unmatched vertex in X. Consider all ''alternating paths'' (paths in G that alternately use edges outside and inside M) starting from u. Let W be the set of vertices in these paths that belong to X (including u itself) and let Z be the set of vertices in these paths that belong to Y. Then every vertex in Z is matched by M to a vertex in W, because an alternating path to an unmatched vertex could be used to increase the size of the matching by toggling whether each of its edges belongs to M or not. Therefore, the size of W is at least the number , Z, of these matched neighbors of Z, plus one for the unmatched vertex u. That is, , W, \ge , Z, +1. However, for every vertex v\in W, every neighbor w of v belongs to Z: an alternating path to w can be found either by removing the matched edge vw from the alternating path to v, or by adding the unmatched edge vw to the alternating path to v. Therefore, Z=N_G(W) and , W, \ge , N_G(W), +1, showing that Hall's condition is violated.


Equivalence of the combinatorial formulation and the graph-theoretic formulation

A problem in the combinatorial formulation, defined by a finite family of finite sets \mathcal F with union X can be translated into a bipartite graph G=(\mathcal F,X,E) where each edge connects a set in \mathcal F to an element of that set. An \mathcal F-perfect matching in this graph defines a system of unique representatives for \mathcal F. In the other direction, from any bipartite graph G=(X,Y,E) one can define a finite family of sets, the family of neighborhoods of the vertices in X, such that any system of unique representatives for this family corresponds to an X-perfect matching in G. In this way, the combinatorial formulation for finite families of finite sets and the graph-theoretic formulation for finite graphs are equivalent. The same equivalence extends to infinite families of finite sets and to certain infinite graphs. In this case, the condition that each set be finite corresponds to a condition that in the bipartite graph G=(X,Y,E), every vertex in X should have finite
degree Degree may refer to: As a unit of measurement * Degree (angle), a unit of angle measurement ** Degree of geographical latitude ** Degree of geographical longitude * Degree symbol (°), a notation used in science, engineering, and mathematics ...
. The degrees of the vertices in Y are not constrained.


Topological proof

Hall's theorem can be proved (non-constructively) based on
Sperner's lemma In mathematics, Sperner's lemma is a combinatorial result on colorings of triangulations, analogous to the Brouwer fixed point theorem, which is equivalent to it. It states that every Sperner coloring (described below) of a triangulation of an ...
.


Applications

The theorem has many applications. For example, for a standard deck of cards, dealt into 13 piles of 4 cards each, the marriage theorem implies that it is possible to select one card from each pile so that the selected cards contain exactly one card of each rank (Ace, 2, 3, ..., Queen, King). More generally, any regular bipartite graph has a perfect matching. More abstractly, let G be a
group A group is a number of persons or things that are located, gathered, or classed together. Groups of people * Cultural group, a group whose members share the same cultural identity * Ethnic group, a group whose members share the same ethnic ide ...
, and H be a finite
index Index (or its plural form indices) may refer to: Arts, entertainment, and media Fictional entities * Index (''A Certain Magical Index''), a character in the light novel series ''A Certain Magical Index'' * The Index, an item on a Halo megastru ...
subgroup In group theory, a branch of mathematics, given a group ''G'' under a binary operation ∗, a subset ''H'' of ''G'' is called a subgroup of ''G'' if ''H'' also forms a group under the operation ∗. More precisely, ''H'' is a subgroup ...
of G. Then the marriage theorem can be used to show that there is a set T such that T is a transversal for both the set of left
coset In mathematics, specifically group theory, a subgroup of a group may be used to decompose the underlying set of into disjoint, equal-size subsets called cosets. There are ''left cosets'' and ''right cosets''. Cosets (both left and right) ...
s and right cosets of H in G. The marriage theorem is used in the usual proofs of the fact that an r\times n
Latin rectangle In combinatorial mathematics, a Latin rectangle is an matrix (where ), using symbols, usually the numbers or as its entries, with no number occurring more than once in any row or column. An Latin rectangle is called a Latin square. An example ...
can always be extended to an (r+1)\times n Latin rectangle when r, and so, ultimately to a
Latin square In combinatorics and in experimental design, a Latin square is an ''n'' × ''n'' array filled with ''n'' different symbols, each occurring exactly once in each row and exactly once in each column. An example of a 3×3 Latin sq ...
.


Logical equivalences

This theorem is part of a collection of remarkably powerful theorems in combinatorics, all of which are related to each other in an informal sense in that it is more straightforward to prove one of these theorems from another of them than from first principles. These include: * The König–Egerváry theorem (1931) (
Dénes Kőnig Dénes Kőnig (September 21, 1884 – October 19, 1944) was a Hungarian mathematician of Jewish heritage who worked in and wrote the first textbook on the field of graph theory. Biography Kőnig was born in Budapest, the son of mathematician Gyu ...
,
Jenő Egerváry Jenő Elek Egerváry (April 16, 1891 – November 30, 1958) was a Hungarian mathematician. Biography Egerváry was born in Debrecen in 1891. In 1914, he received his doctorate at the Pázmány Péter University in Budapest, where he studied und ...
) * König's theorem *
Menger's theorem In the mathematical discipline of graph theory, Menger's theorem says that in a finite graph, the size of a minimum cut set is equal to the maximum number of disjoint paths that can be found between any pair of vertices. Proved by Karl Menger in ...
(1927) * The
max-flow min-cut theorem In computer science and optimization theory, the max-flow min-cut theorem states that in a flow network, the maximum amount of flow passing from the ''source'' to the ''sink'' is equal to the total weight of the edges in a minimum cut, i.e., the ...
(Ford–Fulkerson algorithm) * The
Birkhoff–Von Neumann theorem In mathematics, especially in probability and combinatorics, a doubly stochastic matrix (also called bistochastic matrix) is a square matrix X=(x_) of nonnegative real numbers, each of whose rows and columns sums to 1, i.e., :\sum_i x_=\sum_j x_=1 ...
(1946) *
Dilworth's theorem In mathematics, in the areas of order theory and combinatorics, Dilworth's theorem characterizes the width of any finite partially ordered set in terms of a partition of the order into a minimum number of chains. It is named for the mathematician . ...
. In particular, there are simple proofs of the implications Dilworth's theorem ⇔ Hall's theorem ⇔ König–Egerváry theorem ⇔ König's theorem.


Infinite families


Marshall Hall Jr. variant

By examining
Philip Hall Philip Hall FRS (11 April 1904 – 30 December 1982), was an English mathematician. His major work was on group theory, notably on finite groups and solvable groups. Biography He was educated first at Christ's Hospital, where he won the Thomps ...
's original proof carefully, Marshall Hall Jr. (no relation to Philip Hall) was able to tweak the result in a way that permitted the proof to work for infinite \mathcal S. This variant refines the marriage theorem and provides a lower bound on the number of transversals that a given \mathcal S may have. This variant is: Suppose that (''A''1, ''A''2, ..., ''A''''n''), where the ''A''''i'' are finite sets that need not be distinct, is a family of sets satisfying the marriage condition, and suppose that , ''A''i, ≥ ''r'' for ''i'' = 1, ..., ''n''. Then the number of different transversals for the family is at least ''r''! if ''r'' ≤ ''n'' and ''r''(''r'' − 1) ... (''r'' − ''n'' + 1) if ''r'' > ''n''. Recall that a transversal for a family ''S'' is an ordered sequence, so two different transversals could have exactly the same elements. For instance, the family ''A''1 = , ''A''2 = has both (1, 2) and (2, 1) as distinct transversals.


Marriage condition does not extend

The following example, due to Marshall Hall Jr., shows that the marriage condition will not guarantee the existence of a transversal in an infinite family in which infinite sets are allowed. Let ''S'' be the family, ''A''0 = , ''A''1 = , ''A''2 = , ..., ''A''''i'' = , ... The marriage condition holds for this infinite family, but no transversal can be constructed. The more general problem of selecting a (not necessarily distinct) element from each of a collection of
non-empty In mathematics, the empty set is the unique set having no elements; its size or cardinality (count of elements in a set) is zero. Some axiomatic set theories ensure that the empty set exists by including an axiom of empty set, while in other t ...
sets (without restriction as to the number of sets or the size of the sets) is permitted in general only if the
axiom of choice In mathematics, the axiom of choice, or AC, is an axiom of set theory equivalent to the statement that ''a Cartesian product of a collection of non-empty sets is non-empty''. Informally put, the axiom of choice says that given any collectio ...
is accepted. The marriage theorem does extend to the infinite case if stated properly. Given a bipartite graph with sides ''A'' and ''B'', we say that a subset ''C'' of ''B'' is smaller than or equal in size to a subset ''D'' of ''A'' ''in the graph'' if there exists an injection in the graph (namely, using only edges of the graph) from ''C'' to ''D'', and that it is strictly smaller in the graph if in addition there is no injection in the graph in the other direction. Note that omitting ''in the graph'' yields the ordinary notion of comparing cardinalities. The infinite marriage theorem states that there exists an injection from ''A'' to ''B'' in the graph, if and only if there is no subset ''C'' of ''A'' such that ''N''(''C'') is strictly smaller than ''C'' in the graph.


Fractional matching variant

A ''fractional matching'' in a graph is an assignment of non-negative weights to each edge, such that the sum of weights adjacent to each vertex is at most 1. A fractional matching is ''X''-perfect if the sum of weights adjacent to each vertex is exactly 1. The following are equivalent for a bipartite graph ''G'' = (''X+Y, E''): * ''G'' admits an X-perfect matching. * ''G'' admits an X-perfect fractional matching. The implication follows directly from the fact that ''X''-perfect matching is a special case of an ''X''-perfect fractional matching, in which each weight is either 1 (if the edge is in the matching) or 0 (if it is not). * ''G'' satisfies Hall's marriage condition. The implication holds because, for each subset ''W'' of ''X'', the sum of weights near vertices of ''W'' is , ''W'', , so the edges adjacent to them are necessarily adjacent to at least '', W, '' vertices of ''Y''.


Quantitative variant

When Hall's condition does not hold, the original theorem tells us only that a perfect matching does not exist, but does not tell what is the largest matching that does exist. To learn this information, we need the notion of deficiency of a graph. Given a bipartite graph ''G'' = (''X''+''Y'', ''E''), the ''deficiency of G w.r.t. X'' is the maximum, over all subsets ''W'' of ''X'', of the difference , ''W'', - , ''N''''G''(''W''), . The larger is the deficiency, the farther is the graph from satisfying Hall's condition. Using Hall's marriage theorem, it can be proved that, if the deficiency of a bipartite graph ''G'' is ''d'', then ''G'' admits a matching of size at least , ''X'', -''d''.


Generalizations

* A generalization of Hall's theorem to general graphs (that are not necessarily bipartite) is provided by the
Tutte theorem In the mathematical discipline of graph theory the Tutte theorem, named after William Thomas Tutte, is a characterization of finite graphs with perfect matchings. It is a generalization of Hall's marriage theorem from bipartite to arbitrary graphs ...
. * A generalization of Hall's theorem to
bipartite hypergraph In graph theory, the term bipartite hypergraph describes several related classes of hypergraphs, all of which are natural generalizations of a bipartite graph. Property B and 2-colorability The weakest definition of bipartiteness is also called ...
s is provided by various
Hall-type theorems for hypergraphs In the mathematical field of graph theory, Hall-type theorems for hypergraphs are several generalizations of Hall's marriage theorem from graphs to hypergraphs. Such theorems were proved by Ofra Kessler, Ron Aharoni, Penny Haxell, Roy Meshulam, ...
.


Notes


References

* * * * * * * *


External links


Marriage Theorem
at
cut-the-knot Alexander Bogomolny (January 4, 1948 July 7, 2018) was a Soviet-born Israeli-American mathematician. He was Professor Emeritus of Mathematics at the University of Iowa, and formerly research fellow at the Moscow Institute of Electronics and Math ...

Marriage Theorem and Algorithm
at
cut-the-knot Alexander Bogomolny (January 4, 1948 July 7, 2018) was a Soviet-born Israeli-American mathematician. He was Professor Emeritus of Mathematics at the University of Iowa, and formerly research fellow at the Moscow Institute of Electronics and Math ...

Hall's marriage theorem explained intuitively
at Lucky's notes. {{PlanetMath attribution, id=3059, title=proof of Hall's marriage theorem Matching (graph theory) Theorems in combinatorics Theorems in graph theory Articles containing proofs