arXiv subjects
Publications and source records attributed to Fernando Tura.
A graph is said to be I-eigenvalue free if it has no eigenvalues in the interval I with respect to the adjacency matrix A. In this paper we present two algorithms for generating I-eigenvalue free threshold graphs.
Let $A_n$ be the anti-regular graph of order $n.$ It was conjectured that among all threshold graphs on $n$ vertices, $A_n$ has the smallest positive eigenvalue and the largest eigenvalue less than $-1.$ Recently, in \cite{Cesar2} was given partial results for this conjecture and identified the critical cases where a more refined method is needed. In this paper, we deal with these cases and confirm that conjecture holds.
The eccentricity (anti-adjacency) matrix $\varepsilon(G)$ of a graph $G$ is obtained from the distance matrix by retaining the eccentricities in each row and each column. The $\varepsilon$-eigenvalues of a graph $G$ are those of its eccentricity matrix $\varepsilon(G),$ and the eccentricity energy (or the $\varepsilon$-energy) of $G$ is the sum of the absolute values of $\varepsilon$-eigenvalues. In this paper, we establish some bounds for the $\varepsilon$-energy of the complete multipartite graph $K_{n_1, n_2, \ldots,n_p}$ of order $n= \sum_{i=1}^p n_i $ and characterize the extreme graphs. This partially answers the problem given in Wang {\em et al.} (2019). We finish the paper showing graphs that are not $\varepsilon$-cospectral with the same $\varepsilon$-energy.
A graph is called integral if all the eigenvalues of its adjacency matrix are integers. In this paper, we show a cograph that has a balanced cotree $T_{G}(a_{1},\ldots,a_{r-1},0|0,\ldots,0,a_{r})$ is integral computing its spectrum. As an application, these integral cographs can be used to estimate the eigenvalues of any cograph.
The energy of a graph is defined as the sum the absolute values of the eigenvalues of its adjacency matrix. A threshold graph G on n vertices is coded by a binary sequence of length n. In this paper we answer a question posed by Jacobs et al. [Eigenvalues and energy in threshold graphs, Linear Algebra Appl. 465 (2015) 412-425], by giving an infinite sequences of threshold graphs having the same energy but differ to the complete graph's energy.
Motivated by the linear time algorithm that locates the eigenvalues of a cograph G [10], we investigate the multiplicity of eigenvalue for λ\neq -1,0. For cographs with balanced cotrees we determine explicitly the highest value for the multiplicity.The energy of a graph is defined as the sum of absolute values of the eigenvalues. A graph G on n vertices is said to be borderenergetic if its energy equals the energy of the complete graph Kn. We present families of non-cospectral and borderenergetic cographs.
In this paper we present new L-borderenergetic graphs, this is, graphs which are L-noncospectral with Kn but have the same Laplacian energy. We also present some graphs which are noncospectral to respective normalized Laplacian energy and they have the same normalized Laplacian energy.
In this paper we give a linear time algorithm for computing the number of spanninig trees in double nested graphs.
The energy of a graph is defined as the sum the absolute values of the eigenvalues of its adjacency matrix. A graph G on n vertices is said to be borderenergetic if its energy equals the energy of the complete graph Kn. In this paper, we promote this concept for the Laplacian matrix, introduced by Gutman and Zhou [5]. We say G to be L-borderenergetic if LE(G) = LE(Kn). Several classes of L-borderenergetic graphs are obtained including result that for each positive integer r; there are 2r +1 graphs, of order n = 4r + 4; pairwise L-noncospectral and L-bordernergetic graphs.