Trees with Matrix Weights: Laplacian Matrix and Characteristic-like Vertices

TL;DR

This paper extends the concept of characteristic vertices and algebraic connectivity from trees with positive edge weights to trees with matrix weights, defining Perron values and characteristic-like vertices for these cases.

Contribution

It introduces Perron values and characteristic-like vertices for trees with matrix weights, and derives bounds for Laplacian eigenvalues and computes the Moore-Penrose inverse.

Findings

Existence of characteristic-like vertices in matrix-weighted trees

Lower bounds for Laplacian eigenvalues in these trees

Explicit computation of the Moore-Penrose inverse of the Laplacian

Abstract

It is known that there is an alternative characterization of characteristic vertices for trees with positive weights on their edges via Perron values and Perron branches. Moreover, the algebraic connectivity of a tree with positive edge weights can be expressed in terms of Perron value. In this article, we consider trees with matrix weights on their edges. More precisely, we are interested in trees with the following classes of matrix edge weights: 1. positive definite matrix weights, 2. lower (or upper) triangular matrix weights with positive diagonal entries. For trees with the above classes of matrix edge weights, we define Perron values and Perron branches. Further, we have shown the existence of vertices satisfying properties analogous to the properties of characteristic vertices of trees with positive edge weights in terms of Perron values and Perron branches, and we call such vertices characteristic-like vertices. In this case, the eigenvalues of the Laplacian matrix are nonnegative, and we obtain a lower bound for the first non-zero eigenvalue of the Laplacian matrix in terms of Perron value. Furthermore, we also compute the Moore-Penrose inverse of the Laplacian matrix of a tree with nonsingular matrix weights on its edges.