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In the
mathematical 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 ...
discipline of
graph theory In mathematics, graph theory is the study of ''graphs'', which are mathematical structures used to model pairwise relations between objects. A graph in this context is made up of '' vertices'' (also called ''nodes'' or ''points'') which are conne ...
, Menger's theorem says that in a
finite graph In discrete mathematics, and more specifically in graph theory, a graph is a structure amounting to a Set (mathematics), set of objects in which some pairs of the objects are in some sense "related". The objects correspond to mathematical abstra ...
, 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 Karl Menger (January 13, 1902 – October 5, 1985) was an Austrian-American mathematician, the son of the economist Carl Menger. In mathematics, Menger studied the theory of algebras and the dimension theory of low- regularity ("rough") curves a ...
in 1927, it characterizes the
connectivity Connectivity may refer to: Computing and technology * Connectivity (media), the ability of the social media to accumulate economic capital from the users connections and activities * Internet connectivity, the means by which individual terminals, ...
of a graph. It is generalized by 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 ...
, which is a weighted, edge version, and which in turn is a special case of the strong duality theorem for linear programs.


Edge connectivity

The edge-connectivity version of Menger's theorem is as follows: :Let ''G'' be a finite undirected graph and ''x'' and ''y'' two distinct vertices. Then the size of the minimum edge cut for ''x'' and ''y'' (the minimum number of edges whose removal disconnects ''x'' and ''y'') is equal to the maximum number of pairwise edge-independent paths from ''x'' to ''y''. :Extended to all pairs: a graph is ''k''-edge-connected (it remains connected after removing fewer than ''k'' edges) if and only if every pair of vertices has ''k'' edge-disjoint paths in between.


Vertex connectivity

The vertex-connectivity statement of Menger's theorem is as follows: :Let ''G'' be a finite undirected graph and ''x'' and ''y'' two
nonadjacent This is a glossary of graph theory. Graph theory is the study of graph (discrete mathematics), graphs, systems of nodes or vertex (graph theory), vertices connected in pairs by lines or #edge, edges. Symbols A ...
vertices. Then the size of the minimum
vertex cut In graph theory, a vertex subset is a vertex separator (or vertex cut, separating set) for nonadjacent vertices and if the removal of from the graph separates and into distinct connected components. Examples Consider a grid graph with ...
for ''x'' and ''y'' (the minimum number of vertices, distinct from ''x'' and ''y'', whose removal disconnects ''x'' and ''y'') is equal to the maximum number of pairwise internally vertex-disjoint paths from ''x'' to ''y''. :Extended to all pairs: a graph is ''k''-vertex-connected (it has more than ''k'' vertices and it remains connected after removing fewer than ''k'' vertices) if and only if every pair of vertices has at least ''k'' internally vertex-disjoint paths in between. All these statements (in both edge and vertex versions) remain true in directed graphs (when considering directed paths).


Short proof

Most direct proofs consider a more general statement to allow proving it by induction. It is also convenient to use definitions that include some degenerate cases. The following proof for undirected graphs works without change for directed graphs or multi-graphs, provided we take ''path'' to mean directed path. For sets of vertices ''A,B ⊂ G'' (not necessarily disjoint), an ''AB-path'' is a path in ''G'' with a starting vertex in ''A'', a final vertex in ''B'', and no internal vertices in ''A'' or ''B''. We allow a path with a single vertex in ''A ∩ B'' and zero edges. An ''AB-separator'' of size ''k'' is a set ''S'' of ''k'' vertices (which may intersect ''A'' and ''B'') such that ''G−S'' contains no ''AB''-path. An ''AB-connector'' of size ''k'' is a union of ''k'' vertex-disjoint ''AB''-paths. : Theorem: The minimum size of an ''AB''-separator is equal to the maximum size of an ''AB''-connector. In other words, if no ''k''−1 vertices disconnect ''A'' from ''B'', then there exist ''k'' disjoint paths from ''A'' to ''B''. This variant implies the above vertex-connectivity statement: for ''x,y ∈ G'' in the previous section, apply the current theorem to ''G''− with ''A = N(x)'', ''B = N(y)'', the neighboring vertices of ''x,y''. Then a set of vertices disconnecting ''x'' and ''y'' is the same thing as an ''AB''-separator, and removing the end vertices in a set of independent ''xy''-paths gives an ''AB''-connector. ''Proof of the Theorem:'' Induction on the number of edges in ''G''. For ''G'' with no edges, the minimum ''AB''-separator is ''A ∩ B'', which is itself an ''AB''-connector consisting of single-vertex paths. For ''G'' having an edge ''e'', we may assume by induction that the Theorem holds for ''G−e''. If ''G−e'' has a minimal ''AB''-separator of size ''k'', then there is an ''AB''-connector of size ''k'' in ''G−e'', and hence in ''G''. Otherwise, let ''S'' be a ''AB''-separator of ''G−e'' of size less than ''k'', so that every ''AB''-path in ''G'' contains a vertex of ''S'' or the edge ''e''. The size of ''S'' must be ''k-1'', since if it was less, ''S'' together with either endpoint of ''e'' would be a better ''AB''-separator of ''G''. In ''G−S'' there is an ''AB''-path through ''e'', since ''S'' alone is too small to be an ''AB''-separator of ''G''. Let ''v1'' be the earlier and ''v2'' be the later vertex of ''e'' on such a path. Then ''v1'' is reachable from ''A'' but not from ''B'' in ''G−S−e'', while ''v2'' is reachable from ''B'' but not from ''A''. Now, let ''S1 = S ∪ '', and consider a minimum ''AS1''-separator ''T'' in ''G−e''. Since ''v2'' is not reachable from ''A'' in ''G−S1'', ''T'' is also an ''AS1''-separator in ''G''. Then ''T'' is also an ''AB''-separator in ''G'' (because every ''AB''-path intersects ''S1''). Hence it has size at least ''k''. By induction, ''G−e'' contains an ''AS1''-connector ''C1'' of size ''k''. Because of its size, the endpoints of the paths in it must be exactly ''S1''. Similarly, letting ''S2 = S ∪ '', a minimum ''S2B''-separator has size ''k'', and there is an ''S2B''-connector ''C2'' of size ''k'', with paths whose starting points are exactly ''S2''. Furthermore, since ''S1'' disconnects ''G'', every path in ''C1'' is internally disjoint from every path in ''C2'', and we can define an ''AB''-connector of size ''k'' in ''G'' by concatenating paths (''k−1'' paths through ''S'' and one path going through ''e=v1v2''). Q.E.D.


Other proofs

The directed edge version of the theorem easily implies the other versions. To infer the directed graph vertex version, it suffices to split each vertex ''v'' into two vertices ''v1'', ''v2'', with all ingoing edges going to ''v1'', all outgoing edges going from ''v2'', and an additional edge from ''v1'' to ''v2''. The directed versions of the theorem immediately imply undirected versions: it suffices to replace each edge of an undirected graph with a pair of directed edges (a digon). The directed edge version in turn follows from its weighted variant, 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 ...
. Its proofs are often correctness proofs for max flow algorithms. It is also a special case of the still more general (strong) duality theorem for
linear program Linear programming (LP), also called linear optimization, is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships. Linear programming is ...
s. A formulation that for finite digraphs is equivalent to the above formulation is: : Let ''A'' and ''B'' be sets of vertices in a finite digraph ''G''. Then there exists a family ''P'' of disjoint ''AB''-paths and an ''AB''-separating set that consists of exactly one vertex from each path in ''P''. In this version the theorem follows in fairly easily from Kőnig's theorem: in 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 ...
, the minimal size of a cover is equal to the maximal size of a matching. This is done as follows: replace every vertex ''v'' in the original digraph ''D'' by two vertices ''v' '', ''v'''', and every edge ''uv'' by the edge ''u'v''''; additionally, include the edges ''v'v'''' for every vertex ''v'' that is neither in ''A'' nor ''B''. This results in a bipartite graph, whose one side consists of the vertices ''v' '', and the other of the vertices ''v''''. Applying Kőnig's theorem we obtain a matching ''M'' and a cover ''C'' of the same size. In particular, exactly one endpoint of each edge of ''M'' is in ''C''. Add to ''C'' all vertices ''a'''', for ''a'' in ''A,'' and all vertices ''b' '', for ''b'' in ''B''. Let ''P'' be the set of all ''AB''-paths composed of edges ''uv'' in ''D'' such that ''u'v'''' belongs to M. Let ''Q'' in the original graph consist of all vertices ''v'' such that both ''v' '' and ''v'''' belong to ''C''. It is straightforward to check that ''Q'' is an ''AB''-separating set, that every path in the family ''P'' contains precisely one vertex from ''Q'', and every vertex in ''Q'' lies on a path from ''P'', as desired.


Infinite graphs

Menger's theorem holds for infinite graphs, and in that context it applies to the minimum cut between any two elements that are either vertices or
ends End, END, Ending, or variation, may refer to: End *In mathematics: **End (category theory) ** End (topology) **End (graph theory) ** End (group theory) (a subcase of the previous) **End (endomorphism) *In sports and games ** End (gridiron footbal ...
of the graph . The following result of
Ron Aharoni Ron Aharoni ( he, רון אהרוני ) (born 1952) is an Israeli mathematician, working in finite and infinite combinatorics. Aharoni is a professor at the Technion – Israel Institute of Technology, where he received his Ph.D. in mathematics i ...
and
Eli Berger Eli most commonly refers to: * Eli (name), a given name, nickname and surname * Eli (biblical figure) Eli or ELI may also refer to: Film * ''Eli'' (2015 film), a Tamil film * ''Eli'' (2019 film), an American horror film Music * ''Eli'' (Ja ...
was originally a conjecture proposed by
Paul Erdős Paul Erdős ( hu, Erdős Pál ; 26 March 1913 – 20 September 1996) was a Hungarian mathematician. He was one of the most prolific mathematicians and producers of mathematical conjectures of the 20th century. pursued and proposed problems in ...
, and before being proved was known as the Erdős–Menger conjecture. It is equivalent to Menger's theorem when the graph is finite. :Let ''A'' and ''B'' be sets of vertices in a (possibly infinite) digraph ''G''. Then there exists a family ''P'' of disjoint ''A''-''B''-paths and a separating set which consists of exactly one vertex from each path in ''P''.


See also

*
Gammoid In matroid theory, a field within mathematics, a gammoid is a certain kind of matroid, describing sets of Vertices (graph theory), vertices that can be reached by vertex-disjoint Path (graph theory), paths in a directed graph. The concept of a gam ...
*
k-vertex-connected graph In graph theory, a connected graph is said to be -vertex-connected (or -connected) if it has more than vertices and remains connected whenever fewer than vertices are removed. The vertex-connectivity, or just connectivity, of a graph is the ...
*
k-edge-connected graph In graph theory, a connected graph is -edge-connected if it remains connected whenever fewer than edges are removed. The edge-connectivity of a graph is the largest for which the graph is -edge-connected. Edge connectivity and the enumeration ...
*
Vertex separator In graph theory, a vertex subset is a vertex separator (or vertex cut, separating set) for nonadjacent vertices and if the removal of from the graph separates and into distinct connected components. Examples Consider a grid graph with ...


References


Further reading

* * *


External links


A Proof of Menger's TheoremNetwork flowMax-Flow-Min-Cut
{Dead link, date=March 2020 , bot=InternetArchiveBot , fix-attempted=yes Graph connectivity Network theory Theorems in graph theory