Unistochastic matrix

In mathematics, a unistochastic matrix (also called unitary-stochastic) is a doubly stochastic matrix whose entries are the squares of the absolute values of the entries of some unitary matrix.

A square matrix B of size n is doubly stochastic (or bistochastic) if all its entries are non-negative real numbers and each of its rows and columns sum to 1. It is unistochastic if there exists a unitary matrix U such that

B_{ij}=|U_{ij}|^{2}{\text{ for }}i,j=1,\dots ,n.\,

This definition is analogous to that for an orthostochastic matrix, which is a doubly stochastic matrix whose entries are the squares of the entries in some orthogonal matrix. Since all orthogonal matrices are necessarily unitary matrices, all orthostochastic matrices are also unistochastic. The converse, however, is not true. First, all 2-by-2 doubly stochastic matrices are both unistochastic and orthostochastic, but for larger n this is not the case. For example, take $n=3$ and consider the following doubly stochastic matrix:

B={\frac {1}{2}}{\begin{bmatrix}1&1&0\\0&1&1\\1&0&1\end{bmatrix}}.

This matrix is not unistochastic, since any two vectors with moduli equal to the square root of the entries of two columns (or rows) of B cannot be made orthogonal by a suitable choice of phases. For ${\textstyle n>2}$ , the set of orthostochastic matrices is a proper subset of the set of unistochastic matrices.

Properties

the set of unistochastic matrices contains all permutation matrices
for $n\geq 3$ this set is not convex
for $n=3$ the set of unistochastic matrices is star shaped.
for $n=3$ the relative volume of the set of unistochastic matrices with respect to the Birkhoff polytope of doubly stochastic matrices is $8\pi ^{2}/105\approx 75.2\%$

References

Bengtsson, Ingemar; Ericsson, Åsa; Kuś, Marek; Tadej, Wojciech; Życzkowski, Karol (2005), "Birkhoff's Polytope and Unistochastic Matrices, N = 3 and N = 4", Communications in Mathematical Physics, 259 (2): 307–324, arXiv:math/0402325 , doi:10.1007/s00220-005-1392-8 .
Bengtsson, Ingemar (2004-03-11). "The importance of being unistochastic". arXiv:quant-ph/0403088 .

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