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20182024
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math.CO2024

A cospectral construction for the generalized distance matrix

Ori Friesen, Cecily Kolko, Nick Layman +3

The generalized distance matrix of a graph is a matrix in which the th entry is a function, , of the distance between vertex and vertex . Depending on the choice o…

math.CO2024

Defective eigenvalues of the non-backtracking matrix

Kristin Heysse, Kate Lorenzen, Carolyn Reinhart

We consider graphs for which the non-backtracking matrix has defective eigenvalues, or graphs for which the matrix does not have a full set of eigenvectors. The existence of these…

math.CO2022

On the Edge Derivative of the Normalized Laplacian with Applications to Kemeny's Constant

Connor Albright, Kimberly P. Hadaway, Ari Holcombe Pomerance +3

In a connected graph, Kemeny's constant gives the expected time of a random walk from an arbitrary vertex to reach a randomly-chosen vertex . Because of this, Kemeny's const…

math.CO2020

Cospectral constructions for several graph matrices using cousin vertices

Kate Lorenzen

Graphs can be associated with a matrix according to some rule and we can find the spectrum of a graph with respect to that matrix. Two graphs are cospectral if they have the same s…

math.CO2019

Spectral properties of the exponential distance matrix

Steve Butler, Elizabeth Coper, Aaron Li +2

Given a graph , the exponential distance matrix is defined entry-wise by letting the -entry be , where is the distance between th…

math.CO2018

Graphs that are cospectral for the distance Laplacian

Boris Brimkov, Ken Duna, Leslie Hogben +4

The distance matrix of a graph is the matrix containing the pairwise distances between vertices, and the distance Laplacian matrix is $\mathcal{D}^L(G)=T(G)-\m…