Closed-form formulas for calculating the extremal ranks and inertias of a quadratic matrix-valued function and their applications

TL;DR

This paper derives explicit formulas for the extremal ranks and inertias of quadratic matrix-valued functions and applies them to determine semi-definiteness and optimization conditions in matrix inequalities.

Contribution

It introduces analytical formulas for extremal ranks and inertias of quadratic matrix functions and uses them to establish conditions for semi-definiteness and optimization in matrix inequalities.

Findings

Formulas for maximal and minimal ranks and inertias of quadratic matrix functions.

Necessary and sufficient conditions for semi-definiteness of combined quadratic matrix functions.

Characterization of solutions for L"owner partial ordering optimization problems.

Abstract

This paper presents a group of analytical formulas for calculating the global maximal and minimal ranks and inertias of the quadratic matrix-valued function $\phi(X) = (\, AXB + C\,)M(\, AXB + C)^{*} + D$ and use them to derive necessary and sufficient conditions for the two types of multiple quadratic matrix-valued function {align*} (\, \sum_{i = 1}^{k}A_iX_iB_i + C \,)M(\,\sum_{i = 1}^{k}A_iX_iB_i + C \,)^{*} +D, \ \ \ \sum_{i = 1}^{k}(\,A_iX_iB_i + C_i\,)M_i(\,A_iX_iB_i + C_i \,)^{*} +D {align*} to be semi-definite, respectively, where $A_i,\ B_i,\ C_i,\ C,\ D,\ M_i$ and $M$ are given matrices with $M_i$, $M$ and $D$ Hermitian, $i =1,..., k$. L\"owner partial ordering optimizations of the two matrix-valued functions are studied and their solutions are characterized.