Sharp bounds on distance spectral radius of graphs

Let D(G) denote the distance matrix of a connected graph G. The largest eigenvalue of D(G) is called the distance spectral radius of a graph G, denoted by ?(G). In this article, we give sharp upper and lower bounds for the distance spectral radius and characterize those graphs for which these bounds are best possible.     

Connectivity and minimal distance spectral radius of graphs

In this article, we study how the distance spectral radius behaves when the graph is perturbed by grafting edges. As applications, we also determine the graph with k cut vertices (respectively, k cut edges) with the minimal distance spectral radius.     

The distance spectral radius of trees

The unique graphs with maximum distance spectral radius among trees with given number of vertices of maximum degree and among homeomorphically irreducible trees, respectively, are determined.     

Norm inequalities for the spectral spread of Hermitian operators

In this work, we introduce a new measure for the dispersion of the spectral scale of a Hermitian (self-adjoint) operator acting on a separable infinite-dimensional Hilbert space that we call spectral spread. Then, we obtain some submajorization inequalities involving the spectral spread of self-adjoint operators, that are related to Tao's inequalities for anti-diagonal blocks of positive operators, Kittaneh's commutator inequalities for positive operators and also related to the arithmetic–geometric mean inequality. In turn, these submajorization relations imply inequalities for unitarily invariant norms (in the compact case).     

Some graft transformations and its applications on the distance spectral radius of a graph

Let D(G)=(d_i,j)_n×n denote the distance matrix of a connected graph G with order n, where d_ij is equal to the distance between v_i and v_j in G. The largest eigenvalue of D(G) is called the distance spectral radius of graph G, denoted by ?(G). In this paper, some graft transformations that decrease or increase ?(G) are given. With them, for the graphs with both order n and k pendant vertices, the extremal graphs with the minimum distance spectral radius are completely characterized; the extremal graph with the maximum distance spectral radius is shown to be a dumbbell graph (obtained by attaching some pendant edges to each pendant vertex of a path respectively) when 2≤k≤n−2; for k=1,2,3,n−1, the extremal graphs with the maximum distance spectral radius are completely characterized.     

A generalized infectious model induced by the contacting distance (CTD)

The aim of this paper is to theoretically study the effect of the contacting distance (CTD) between the susceptible and infectious individuals in controlling infectious diseases. This paper formulates a generalized SEIR model incorporating the effect of the contacting distance (CTD). The dynamical behaviors of the proposed model are investigated and the controlling measures of the infectious diseases are developed. The results show that the contacting distance (CTD) between the susceptible and infectious individuals plays an important role in controlling infectious diseases. Some diseases will be globally controlled when the contacting distance (CTD) is larger than the threshold value. That is to say, the long contacting distance (CTD) implies the corresponding diseases will be controlled. However, for other diseases, the long or short contacting distance (CTD) will induce them to spread and be endemic. The moderate contacting distance (CTD) may be beneficial to control these diseases. Therefore, the appropriate contacting distance (CTD) should be selected for the given diseases in order to control the corresponding infectious diseases. Finally, a special numerical experiment is given to test our results. These results give some theoretical and experimental guides for the disease control authorities.     

The limiting normality of the test statistic for the two-sample problem induced by a convex sum distance

Critchlow (1992, J. Statist. Plann. Inference, 32, 325–346) proposed a method of a unified construction of a class of rank tests. In this paper, we introduce a convex sum distance and prove the limiting normality of the test statistics for the two-sample problem derived by his method.     

On accuracy of approximation of the spectral radius by the Gelfand formula

The famous Gelfand formula ρ(A)=limsup_n→∞A^n1/n for the spectral radius of a matrix is of great importance in various mathematical constructions. Unfortunately, the range of applicability of this formula is substantially restricted by a lack of estimates for the rate of convergence of the quantities A^n1/n to ρ(A). In the paper this deficiency is made up to some extent. By using the Bochi inequalities we establish explicit computable estimates for the rate of convergence of the quantities A^n1/n to ρ(A). The obtained estimates are then extended for evaluation of the joint spectral radius of matrix sets.     

A spectral notion of Gromov–Wasserstein distance and related methods

We introduce a spectral notion of distance between objects and study its theoretical properties. Our distance satisfies the properties of a metric on the class of isometric shapes, which means, in particular, that two shapes are at 0 distance if and only if they are isometric when endowed with geodesic distances. Our construction is similar to the Gromov–Wasserstein distance, but rather than viewing shapes merely as metric spaces, we define our distance via the comparison of heat kernels. This allows us to establish precise relationships of our distance to previously proposed spectral invariants used for data analysis and shape comparison, such as the spectrum of the Laplace–Beltrami operator, the diagonal of the heat kernel, and certain constructions based on diffusion distances. In addition, the heat kernel encodes a natural notion of scale, which is useful for multi-scale shape comparison. We prove a hierarchy of lower bounds for our distance, which provide increasing discriminative power at the cost of an increase in computational complexity. We also explore the definition of other spectral metrics on collections of shapes and study their theoretical properties.     

Distance signless Laplacian spectral radius and Hamiltonian properties of graphs

In this paper, we establish a sufficient condition on distance signless Laplacian spectral radius for a bipartite graph to be Hamiltonian. We also give two sufficient conditions on distance signless Laplacian spectral radius for a graph to be Hamilton-connected and traceable from every vertex, respectively. Furthermore, we obtain a sufficient condition for a graph to be Hamiltonian in terms of the distance signless Laplacian spectral radius of the complement of a graph G.     

On the size of the fibers of spectral maps induced by semialgebraic embeddings

Let be the ring of (continuous) semialgebraic functions on a semialgebraic set M and its subring of bounded semialgebraic functions. In this work we compute the size of the fibers of the spectral maps and induced by the inclusion of a semialgebraic subset N of M. The ring can be understood as the localization of at the multiplicative subset of those bounded semialgebraic functions on M with empty zero set. This provides a natural inclusion that reduces both problems above to an analysis of the fibers of the spectral map . If we denote , it holds that the restriction map is a homeomorphism. Our problem concentrates on the computation of the size of the fibers of at the points of Z. The size of the fibers of prime ideals “close” to the complement provides valuable information concerning how N is immersed inside M. If N is dense in M, the map is surjective and the generic fiber of a prime ideal contains infinitely many elements. However, finite fibers may also appear and we provide a criterium to decide when the fiber is a finite set for . If such is the case, our procedure allows us to compute the size s of . If in addition N is locally compact and M is pure dimensional, s coincides with the number of minimal prime ideals contained in .     

On the distance and distance signless Laplacian spectral radii of bicyclic graphs

The unique graphs with minimum and second-minimum distance (distance signless Laplacian, respectively) spectral radii are determined among bicyclic graphs with fixed number of vertices.     

Sharp bounds on the distance spectral radius and the distance energy of graphs

The D-eigenvalues {μ₁,μ₂,…,…,μ_p} of a graph G are the eigenvalues of its distance matrix D and form the D-spectrum of G denoted by spec_D(G). The greatest D-eigenvalue is called the D-spectral radius of G denoted by μ₁. The D-energy E_D(G) of the graph G is the sum of the absolute values of its D-eigenvalues. In this paper we obtain some lower bounds for μ₁ and characterize those graphs for which these bounds are best possible. We also obtain an upperbound for E_D(G) and determine those maximal D-energy graphs.