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. Jump up to: 2.0 2.1 Spectral Properties of Totally Positive Kernels and Matrices, Allan Pinkus

Further reading

External links