Nonpositive Eigenvalues of the Adjacency Matrix and Lower Bounds for Laplacian Eigenvalues
Combinatorics
2012-05-29 v3
Abstract
Let be the smallest number such that the adjacency matrix of any undirected graph with vertices or more has at least nonpositive eigenvalues. We show that is well-defined and prove that the values of for are respectively. In addition, we prove that for all , , in which is the Ramsey number for and , and is the triangular number. This implies new lower bounds for eigenvalues of Laplacian matrices: the -th largest eigenvalue is bounded from below by the -th largest degree, which generalizes some prior results.
Cite
@article{arxiv.1108.4810,
title = {Nonpositive Eigenvalues of the Adjacency Matrix and Lower Bounds for Laplacian Eigenvalues},
author = {Zachary B. Charles and Miriam Farber and Charles R. Johnson and Lee Kennedy-Shaffer},
journal= {arXiv preprint arXiv:1108.4810},
year = {2012}
}
Comments
23 pages, 12 figures