Eigenbounds of symmetric positive definite tensors
For researchers in tensor analysis and nonlinear systems, this provides a new invariant-based method for eigenvalue bounds that is more robust than existing coordinate-dependent approaches.
The paper introduces an algebraic framework using trace and determinant invariants to derive eigenvalue bounds for symmetric positive definite tensors via AM-GM inequalities, outperforming classical Gershgorin bounds, especially for tensors with negative off-diagonal entries and higher orders. The bounds are validated by certifying positive definiteness of Lyapunov functions in nonlinear system stability analysis.
This article introduces an algebraic framework for establishing eigenvalue bounds for symmetric positive definite tensors by leveraging intrinsic invariants, specifically the trace and determinant (resultant). We derive a hierarchy of inequalities via the Arithmetic Mean-Geometric Mean (AM-GM) inequality that yields progressively tighter upper and lower bounds for the tensor spectral radius and smallest eigenvalue. A comprehensive comparative analysis demonstrates that our invariant-based approach significantly outperforms classical coordinate-dependent methods such as the Gershgorin circle theorem. We explicitly show that our bounds remain robust and informative in scenarios where Gershgorin bounds fail, particularly for tensors with negative off-diagonal entries, where algebraic cancellations occur, and higher-order tensors, where combinatorial growth leads to loose estimates. Furthermore, we validate the practical utility of these bounds by applying them to certify the positive definiteness of Lyapunov functions in the stability analysis of nonlinear autonomous systems.