Totally positive matrix

In mathematics, a totally positive matrix is a square matrix in which the determinant of every square submatrix, including the minors, is not negative.^[1] A totally positive matrix also has all nonnegative eigenvalues.

Definition

Let

$\bold{A} = (A_{ij})$

be an n × n matrix, where n, p, k, ℓ are all integers so that:

$\begin{align} & \bold{A}_{[p]} = (A_{i_kj_\ell})\\ & {1 \leq i_k, j_\ell \leq n \text{ for }1 \leq k, \ell \leq p} \end{align}$

Then A a totally positive matrix if:^[2]

$\det(\bold{A}_{[p]}) \geq 0$

for all p. Each integer p corresponds to a p × p submatrix of A.

History

Topics which historically led to the development of the theory of total positivity include the study of:^[2]

• the spectral properties of kernels and matrices which are totally positive,
• ordinary differential equations whose Green's function is totally positive (by M. G. Krein and some colleagues in the mid-1930s),
• the variation diminishing properties (started by I. J. Schoenberg in 1930),
• Pólya frequency functions (by I. J. Schoenberg in the late 1940s and early 1950s).

Examples

For example, a Vandermonde matrix whose nodes are positive and increasing is a totally positive matrix.

See also

• Compound matrix

References

1. ↑ George M. Phillips (2003), "Total Positivity", Interpolation and Approximation by Polynomials, Springer, p. 274, ISBN 9780387002156
2. ↑ 2.0 2.1 Spectral Properties of Totally Positive Kernels and Matrices, Allan Pinkus

Further reading

• Allan Pinkus (2009), Totally Positive Matrices, Cambridge University Press, ISBN 9780521194082

External links

• Spectral Properties of Totally Positive Kernels and Matrices, Allan Pinkus
• Parametrizations of Canonical Bases and Totally Positive Matrices, Arkady Berenstein
• Tensor Product Multiplicities, Canonical Bases And Totally Positive Varieties (2001), A. Berenstein , A. Zelevinsky