Birkhoff–von Neumann theorem
E637943
The Birkhoff–von Neumann theorem is a fundamental result in matrix theory and combinatorics stating that every doubly stochastic matrix can be expressed as a convex combination of permutation matrices.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Birkhoff–von Neumann theorem canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T7059218 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
Target entity: Birkhoff–von Neumann theorem Context triple: [Garrett Birkhoff, notableConcept, Birkhoff–von Neumann theorem]
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A.
Szekeres–Lindström theorem
The Szekeres–Lindström theorem is a result in combinatorics that characterizes the maximum size of intersecting families of subsets, serving as a precursor to and special case of the Erdős–Ko–Rado theorem.
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B.
Gleason’s theorem
Gleason’s theorem is a foundational result in the mathematical formulation of quantum mechanics that characterizes all probability measures on the lattice of projection operators in a Hilbert space, effectively justifying the Born rule.
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C.
de Bruijn–van Aardenne–Ehrenfest theorem
The de Bruijn–van Aardenne–Ehrenfest theorem is a fundamental result in combinatorics that characterizes the number of Eulerian circuits in directed graphs, particularly de Bruijn graphs, and underpins constructions in coding theory and discrete mathematics.
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D.
Gelfand–Naimark theorem
The Gelfand–Naimark theorem is a foundational result in functional analysis that characterizes C*-algebras as algebras of bounded operators on a Hilbert space (and, in the commutative case, as algebras of continuous functions on a locally compact Hausdorff space).
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E.
Erdős–Ko–Rado theorem
The Erdős–Ko–Rado theorem is a fundamental result in extremal combinatorics that determines the maximum size of a family of subsets of a finite set in which every pair of subsets has a non-empty intersection.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Birkhoff–von Neumann theorem Target entity description: The Birkhoff–von Neumann theorem is a fundamental result in matrix theory and combinatorics stating that every doubly stochastic matrix can be expressed as a convex combination of permutation matrices.
-
A.
Szekeres–Lindström theorem
The Szekeres–Lindström theorem is a result in combinatorics that characterizes the maximum size of intersecting families of subsets, serving as a precursor to and special case of the Erdős–Ko–Rado theorem.
-
B.
Gleason’s theorem
Gleason’s theorem is a foundational result in the mathematical formulation of quantum mechanics that characterizes all probability measures on the lattice of projection operators in a Hilbert space, effectively justifying the Born rule.
-
C.
de Bruijn–van Aardenne–Ehrenfest theorem
The de Bruijn–van Aardenne–Ehrenfest theorem is a fundamental result in combinatorics that characterizes the number of Eulerian circuits in directed graphs, particularly de Bruijn graphs, and underpins constructions in coding theory and discrete mathematics.
-
D.
Gelfand–Naimark theorem
The Gelfand–Naimark theorem is a foundational result in functional analysis that characterizes C*-algebras as algebras of bounded operators on a Hilbert space (and, in the commutative case, as algebras of continuous functions on a locally compact Hausdorff space).
-
E.
Erdős–Ko–Rado theorem
The Erdős–Ko–Rado theorem is a fundamental result in extremal combinatorics that determines the maximum size of a family of subsets of a finite set in which every pair of subsets has a non-empty intersection.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
mathematical theorem
ⓘ
theorem in matrix theory ⓘ |
| alsoKnownAs | Birkhoff theorem on doubly stochastic matrices NERFINISHED ⓘ |
| appliesTo | finite square matrices ⓘ |
| assumes |
column sums of the matrix equal 1
ⓘ
matrix entries are nonnegative real numbers ⓘ row sums of the matrix equal 1 ⓘ |
| author |
Garrett Birkhoff
NERFINISHED
ⓘ
John von Neumann NERFINISHED ⓘ |
| characterizes | Birkhoff polytope as convex hull of permutation matrices ⓘ |
| concerns |
n×n doubly stochastic matrices
ⓘ
n×n permutation matrices ⓘ |
| conclusion | matrix is a convex combination of permutation matrices ⓘ |
| describes | structure of doubly stochastic matrices ⓘ |
| equivalentTo | statement that extreme points of the Birkhoff polytope are permutation matrices ⓘ |
| field |
combinatorics
ⓘ
linear algebra ⓘ matrix theory ⓘ polyhedral combinatorics ⓘ |
| hasConsequence |
doubly stochastic matrices form a polytope
ⓘ
every doubly stochastic matrix is a finite convex combination of permutation matrices ⓘ vertices of the Birkhoff polytope are permutation matrices ⓘ |
| implies | The set of doubly stochastic matrices is the convex hull of permutation matrices. ⓘ |
| involves |
convex hull
ⓘ
extreme points of a polytope ⓘ |
| namedAfter |
Garrett Birkhoff
NERFINISHED
ⓘ
John von Neumann NERFINISHED ⓘ |
| relatedTo |
Carathéodory's theorem
NERFINISHED
ⓘ
Hall's marriage theorem NERFINISHED ⓘ polytope theory ⓘ |
| relatesConcept |
Birkhoff polytope
NERFINISHED
ⓘ
assignment problem ⓘ bipartite graph perfect matchings ⓘ convex combination ⓘ doubly stochastic matrix ⓘ permutation matrix ⓘ transportation problem ⓘ |
| statement | Every doubly stochastic matrix can be expressed as a convex combination of permutation matrices. ⓘ |
| typeOfResult |
extreme point characterization
ⓘ
representation theorem ⓘ |
| usedIn |
combinatorial optimization
ⓘ
design of randomized algorithms ⓘ matrix scaling and decomposition ⓘ network flow theory ⓘ quantum information theory ⓘ statistics ⓘ |
| yearProved | 1946 ⓘ |
How these facts were elicited
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Subject: Birkhoff–von Neumann theorem Description of subject: The Birkhoff–von Neumann theorem is a fundamental result in matrix theory and combinatorics stating that every doubly stochastic matrix can be expressed as a convex combination of permutation matrices.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.