Doubly stochastic matrix

In mathematics, especially in probability and combinatorics, a doubly stochastic matrix (also called bistochastic),is a square matrix A = ( a i j ) {displaystyle A=(a_{ij})} of nonnegative real numbers, each of whose rows and columns sums to 1, i.e., In mathematics, especially in probability and combinatorics, a doubly stochastic matrix (also called bistochastic),is a square matrix A = ( a i j ) {displaystyle A=(a_{ij})} of nonnegative real numbers, each of whose rows and columns sums to 1, i.e., Thus, a doubly stochastic matrix is both left stochastic and right stochastic. Indeed, any matrix that is both left and right stochastic must be square: if every row sums to one then the sum of all entries in the matrix must be equal to the number of rows, and since the same holds for columns, the number of rows and columns must be equal. The class of n × n {displaystyle n imes n} doubly stochastic matrices is a convex polytope known as the Birkhoff polytope B n {displaystyle B_{n}} . Using the matrix entries as Cartesian coordinates, it lies in an ( n − 1 ) 2 {displaystyle (n-1)^{2}} -dimensional affine subspace of n 2 {displaystyle n^{2}} -dimensional Euclidean space defined by 2 n − 1 {displaystyle 2n-1} independent linear constraints specifying that the row and column sums all equal one. (There are 2 n − 1 {displaystyle 2n-1} constraints rather than 2 n {displaystyle 2n} because one of these constraints is dependent, as the sum of the row sums must equal the sum of the column sums.) Moreover, the entries are all constrained to be non-negative and less than or equal to one. The Birkhoff–von Neumann theorem states that this polytope B n {displaystyle B_{n}} is the convex hull of the set of n × n {displaystyle n imes n} permutation matrices, and furthermore that the vertices of B n {displaystyle B_{n}} are precisely the permutation matrices. In other words, if A {displaystyle A} is doubly stochastic matrix, then there exist θ 1 , … , θ k ≥ 0 , ∑ i = 1 k θ i = 1 {displaystyle heta _{1},ldots , heta _{k}geq 0,sum _{i=1}^{k} heta _{i}=1} and permutation matrices P 1 , … , P k {displaystyle P_{1},ldots ,P_{k}} such that This representation is known as the Birkhoff–von Neumann decomposition, and it may not be unique in general. By Marcus-Ree theorem, however, there need not be more than n 2 − 2 n + 2 {displaystyle n^{2}-2n+2} terms in any decomposition, namely In other words, while there exists a decomposition with n ! {displaystyle n!} permutation matrices, there is at least one constructible decomposition with no more than ( n − 1 ) 2 + 1 {displaystyle (n-1)^{2}+1} matrices. The problem of computing the representation with the minimum number of terms has been shown to be NP-hard, but some heuristics for computing it are known. This theorem can be extended for the general stochastic matrix with deterministic transition matrices.