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Random graphs are more and more used for modeling real world networks such as evolutionary networks of proteins. For this purpose we look at two different models and analyze how properties like connectedness and degree distributions are…

Probability · Mathematics 2019-02-05 Klemens Taglieber , Uta Freiberg

A simple and accurate relationship is demonstrated that links the average shortest path, nodes, and edges in a complex network. This relationship takes advantage of the concept of link density and shows a large improvement in fitting…

Physics and Society · Physics 2013-04-24 Reginald D. Smith

In this paper, we consider the distance spectra of the derangement graphs. First we give a constructive proof that the connected derangement graphs are of diameter 2. Then we obtain their distance spectra. In particular, we determine all…

Combinatorics · Mathematics 2016-10-24 Yunnan Li , Huiqiu Lin

The microscopic and macroscopic dynamics of random networks is investigated in the strong-dilution limit (i.e. for sparse networks). By simulating chaotic maps, Stuart-Landau oscillators, and leaky integrate-and-fire neurons, we show that a…

Disordered Systems and Neural Networks · Physics 2012-12-24 Stefano Luccioli , Simona Olmi , Antonio Politi , Alessandro Torcini

Recent spectral graph sparsification research allows constructing nearly-linear-sized subgraphs that can well preserve the spectral (structural) properties of the original graph, such as the first few eigenvalues and eigenvectors of the…

Data Structures and Algorithms · Computer Science 2020-05-04 Ying Zhang , Zhiqiang Zhao , Zhuo Feng

Both sampling a time-varying signal, and its spectral analysis are activities subjected to theoretically compelling, such as Shannon's theorem and the objectively limiting of the frequency's resolution. Usually, the signals' spectra are…

Numerical Analysis · Computer Science 2015-05-25 Cezar Doca , Constantin Paunoiu

A general analytical approach to the statistical description of quantum graph spectra based on the exact periodic orbit expansions of quantum levels is discussed. The exact and approximate expressions obtained in \cite{Anima} for the…

Quantum Physics · Physics 2007-05-23 Yu. Dabaghian

We investigate the impact of degree-degree correlations on the spectra of networks. Even though density distributions exhibit drastic changes depending on the (dis)assortative mixing and the network architecture, the short range…

Physics and Society · Physics 2015-02-06 Sarika Jalan , Alok Yadav

We describe the structure of connected graphs with the minimum and maximum average distance, radius, diameter, betweenness centrality, efficiency and resistance distance, given their order and size. We find tight bounds on these graph…

Molecular Networks · Quantitative Biology 2011-05-02 Dionysios Barmpoutis , Richard M. Murray

Using methods from algebraic graph theory and convex optimization, we study the relationship between local structural features of a network and spectral properties of its Laplacian matrix. In particular, we derive expressions for the…

Optimization and Control · Mathematics 2016-11-17 Victor M. Preciado , Ali Jadbabaie , George C. Verghese

We are interested in the general question: to what extent are the spectral properties of a graph connected to the distance function? Our motivation is a concrete example of this question that is due to Steinerberger. We provide some…

Combinatorics · Mathematics 2020-11-19 Kelly B Yancey , Matthew Yancey

While sparse inverse covariance matrices are very popular for modeling network connectivity, the value of the dense solution is often overlooked. In fact the L2-regularized solution has deep connections to a number of important applications…

Machine Learning · Computer Science 2019-03-19 Keith Dillon

The adjacency operator of a graph has a spectrum and a class of scalar-valued spectral measures which have been systematically analyzed; it also has a spectral multiplicity function which has been less studied. The first purpose of this…

Combinatorics · Mathematics 2024-03-06 Pierre de la Harpe

We take on a Random Matrix theory viewpoint to study the spectrum of certain reversible Markov chains in random environment. As the number of states tends to infinity, we consider the global behavior of the spectrum, and the local behavior…

Probability · Mathematics 2010-06-15 Charles Bordenave , Pietro Caputo , Djalil Chafai

We investigate connections between the symmetries (automorphisms) of a graph and its spectral properties. Whenever a graph has a symmetry, i.e. a nontrivial automorphism $\phi$, it is possible to use $\phi$ to decompose any matrix…

Combinatorics · Mathematics 2016-10-07 Wayne Barrett , Amanda Francis , Ben Webb

We propose and investigate a unifying class of sparse random graph models, based on a hidden coloring of edge-vertex incidences, extending an existing approach, Random graphs with a given degree distribution, in a way that admits a…

Statistical Mechanics · Physics 2009-11-10 Bo Söderberg

We consider each of the three classes of representations of cyclic groups that arise in the study of rational sphere maps. We study the possible number of terms for invariant polynomials with non-negative coefficients that are constant on…

Complex Variables · Mathematics 2025-12-08 John P. D'Angelo , Dusty E. Grundmeier , Daniel A. Lichtblau

We study the spectral linear elasticity problem in an unbounded periodic waveguide, which consists of a sequence of identical bounded cells connected by thin ligaments of diameter of order $ h >0$. The essential spectrum of the problem is…

Spectral Theory · Mathematics 2017-09-13 F. L. Bakharev , J. Taskinen

We investigate the properties of sparse matrix ensembles with particular regard for the spectral ergodicity hypothesis, which claims the identity of ensemble and spectral averages of spectral correlators. An apparent violation of the…

Condensed Matter · Physics 2009-10-31 A. D. Jackson , C. Mejia-Monasterio , T. Rupp , M. Saltzer , T. Wilke

How does coarsening affect the spectrum of a general graph? We provide conditions such that the principal eigenvalues and eigenspaces of a coarsened and original graph Laplacian matrices are close. The achieved approximation is shown to…

Machine Learning · Computer Science 2018-02-22 Andreas Loukas , Pierre Vandergheynst