We analyze the spectral distribution of the adjacency matrix and the graph Laplacian for a wide variety of random trees. Using soft arguments which seem to be applicable in a wide variety of settings, we show that the empirical spectral distribution for a number of random tree models, converges to a constant (model dependent) distribution. We also analyze the kernel of the spectrum and prove as...

Let G be a simple graph and let its vertex set be V (G) = {v1, v2, ..., vn}. The adjacency matrix A(G) of the graph G is a square matrix of order n whose (i, j)-entry is equal to unity if the vertices vi and vj are adjacent, and is equal to zero otherwise. The eigenvalues λ1, λ2, ..., λn of A(G), assumed in non increasing order, are the eigenvalues of the graph G. The energy of G was first defi...

This paper is about counting lattice paths. Examples are the paths counted by Catalan, Motzkin or Schröder numbers. We identify lattice paths with walks on some path-like graph. The entries of the nth power of the adjacency matrix are the number of paths of length nwith prescribed start and end position. The adjacency matrices turn out to be Toeplitz matrices. Explicit expressions for eigenvalu...

In mathematical chemistry, the median eigenvalues of the adjacency matrix of a molecular graph are strictly related to orbital energies and molecular orbitals. In this regard, the difference between the occupied orbital of highest energy (HOMO) and the unoccupied orbital of lowest energy (LUMO) has been investigated (see Fowler and Pisansky in Acta Chim. Slov. 57:513-517, 2010). Motivated by th...

‎Let $Gamma$ be a graph with adjacency eigenvalues $lambda_1leqlambda_2leqldotsleqlambda_n$‎. ‎Then the energy of‎ ‎$Gamma$‎, ‎a concept defined in 1978 by Gutman‎, ‎is defined as $mathcal{E}(G)=sum_{i=1}^n|lambda_i|$‎. ‎Also‎ ‎the Estrada index of $Gamma$‎, ‎which is defined in 2000 by Ernesto Estrada‎, ‎is defined as $EE(Gamma)=sum_{i=1}^ne^{lambda_i}$‎. ‎In this paper‎, ‎we compute the eigen...

The anti-adjacency matrix of a graph is constructed from the distance by keeping each row and column only largest distances. This can be interpreted as opposite adjacency matrix, which instead in distances equal to 1. (anti-)adjacency eigenvalues are those its matrix. Employing novel technique introduced Haemers (2019) [9], we characterize all connected graphs with exactly one positive eigenval...

In this paper we investigate eigenvalues of matrix representations of trees as a means by which one might quantify the shape of a tree. We consider the adjacency matrix, the Laplacian matrix, and the pairwise distance matrix of the tree. We then demonstrate that for any of these choices of matrix the fraction of trees with a unique set of eigenvalues goes to zero as the number of leaves goes to...

Let $S(G^{sigma})$ be the skew-adjacency matrix of the oriented graph $G^{sigma}$, which is obtained from a simple undirected graph $G$ by assigning an orientation $sigma$ to each of its edges. The skew energy of an oriented graph $G^{sigma}$ is defined as the sum of absolute values of all eigenvalues of $S(G^{sigma})$. Two oriented graphs are said to be skew equienergetic iftheir skew energies...

A threshold graph on n vertices is coded by a binary string of length n − 1. We obtain a formula for the inertia of (the adjacency matrix of) a threshold graph in terms of the code of the graph. It is shown that the number of negative eigenvalues of the adjacency matrix of a threshold graph is the number of ones in the code, whereas the nullity is given by the number of zeros in the code that a...