Spectral and Nilpotent Matrix Orderings: Comparison and Applications in Dynamic Systems

Abstract

In our earlier work, we proposed the \emph{Spectral and Nilpotent Ordering} (SNO) as a new framework that extends matrix comparison beyond the Hermitian setting by incorporating both spectral and nilpotent structures. Building on that foundation, the present paper develops concrete certificates and applications of SNO. First, we employ generalized Gershgorin theorems to design certificates for spectral ordering that avoid direct eigenvalue computation and analyze their robustness under perturbations. Second, we introduce rank-based criteria that provide certificates for ordering the nilpotent parts of matrices without requiring a full Jordan decomposition. Finally, we apply the SNO framework to linear dynamical systems, where we construct a hierarchy of stability orderings that capture both asymptotic and transient behaviors. These contributions advance the theoretical underpinnings of SNO and demonstrate its potential as a versatile tool for operator analysis, computational methods, and stability studies in complex systems.