Totally positive matrix

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In mathematics, a totally positive matrix is a square matrix in which all the minors are positive: that is, the determinant of every square submatrix is a positive number.[1] A totally positive matrix has all entries positive, so it is also a positive matrix; and it has all principal minors positive (and positive eigenvalues). A symmetric totally positive matrix is therefore also positive-definite. A totally non-negative matrix is defined similarly, except that all the minors must be non-negative (positive or zero). Some authors use "totally positive" to include all totally non-negative matrices.

Definition

Let [math]\displaystyle{ \mathbf{A} = (A_{ij})_{ij} }[/math] be an n × n matrix. Consider any [math]\displaystyle{ p\in\{1,2,\ldots,n\} }[/math] and any p × p submatrix of the form [math]\displaystyle{ \mathbf{B} = (A_{i_kj_\ell})_{k\ell} }[/math] where:

[math]\displaystyle{ 1\le i_1 \lt \ldots \lt i_p \le n,\qquad 1\le j_1 \lt \ldots \lt j_p \le n. }[/math]

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

[math]\displaystyle{ \det(\mathbf{B}) \gt 0 }[/math]

for all submatrices [math]\displaystyle{ \mathbf{B} }[/math] that can be formed this way.

History

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

Examples

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

See also

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

External links