Determinant Bounds for $(n-1)$-Locally Positive Semidefinite Matrices

TL;DR

This paper establishes sharp determinant bounds for matrices that are locally positive semidefinite but not necessarily globally, extending classical inequalities and quantifying their deviation from positive semidefiniteness.

Contribution

It derives new sharp lower bounds on determinants of locally positive semidefinite matrices and extends classical inequalities like Fisher and Koteljanskii bounds.

Findings

Derived sharp lower bounds for determinants of locally positive semidefinite matrices.

Extended classical determinant inequalities to the local positive semidefinite setting.

Quantified the gap between local and global positive semidefiniteness using determinant bounds.

Abstract

In this framework, the extremal case corresponds to the tightest nontrivial relaxation in this hierarchy, in which every proper principal submatrix is constrained to be positive semidefinite, while the global positive semidefiniteness condition is governed by the determinant. In this paper, we study the determinants of locally positive semidefinite matrices and derive sharp lower bounds on their determinants that quantify the gap between local and global positive semidefiniteness. We further obtain analogous extensions of classical determinant inequalities, including Fisher and Koteljanskii inequalities, providing tight lower bounds in each case. In a sense, these results quantify, via determinant bounds, how far the class of locally positive semidefinite matrices can be from being positive semidefinite.