New graph invariants based on p-Laplacian eigenvalues

Abstract

We present monotonicity inequalities for certain functions involving eigenvalues of p-Laplacians on signed graphs with respect to p. Inspired by such monotonicity, we propose new spectrum-based graph invariants, called (variational) cut-off adjacency eigenvalues, that are relevant to certain eigenvector-dependent nonlinear eigenvalue problem. Using these invariants, we obtain new lower bounds for the p-Laplacian variational eigenvalues, essentially giving the state-of-the-art spectral asymptotics for these eigenvalues. Moreover, based on such invariants, we establish two inertia bounds regarding the cardinalities of a maximum independent set and a minimum edge cover, respectively. The first inertia bound enhances the classical Cvetkovi\'c bound, and the second one implies that the k-th p-Laplacian variational eigenvalue is of the order 2p as p tends to infinity whenever k is larger than the cardinality of a minimum edge cover of the underlying graph. We further discover an interesting connection between graph p-Laplacian eigenvalues and tensor eigenvalues and discuss applications of our invariants to spectral problems of tensors.

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