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The energy level statistics of uniform random graphs are studied, by treating the graphs as random tight-binding lattices. The inherent random geometry of the graphs and their dynamical spatial dimensionality, leads to various quantum…

Disordered Systems and Neural Networks · Physics 2024-12-20 Ioannis Kleftogiannis , Ilias Amanatidis

Spatial networks are networks where nodes are located in a space equipped with a metric. Typically, the space is two-dimensional and until recently and traditionally, the metric that was usually considered was the Euclidean distance. In…

Combinatorics · Mathematics 2022-11-29 Ramon Ferrer-i-Cancho

We investigate quantum random tensor network states where the bond dimensions scale polynomially with the system size, $N$. Specifically, we examine the delocalization properties of random Matrix Product States (RMPS) in the computational…

Quantum Physics · Physics 2025-01-22 Guglielmo Lami , Jacopo De Nardis , Xhek Turkeshi

We examine the fundamental question whether a random discrete structure with the minimal number of restrictions can converge to continuous metric space. We study the geometrical properties such as the dimensionality and the curvature…

Disordered Systems and Neural Networks · Physics 2024-05-14 Ioannis Kleftogiannis , Ilias Amanatidis

In a tight binding framework, we analyze the characteristics of electronic states in strongly disordered materials (hopping sites are placed randomly with no local order) with tunneling matrix elements decaying exponentially in the atomic…

Materials Science · Physics 2012-02-01 D. J. Priour

Systems which consist of many localized constituents interacting with each other can be represented by complex networks. Consistently, network science has become highly popular in vast fields focusing on natural, artificial and social…

Statistical Mechanics · Physics 2022-06-29 Rute Oliveira , Samuraí Brito , Luciano R. da Silva , Constantino Tsallis

We delve into the statistical properties of regions within complex networks that are distant from vertices with high centralities, such as hubs or highly connected clusters. These remote regions play a pivotal role in shaping the asymptotic…

Physics and Society · Physics 2023-10-23 J. G. Oliveira , S. N. Dorogovtsev , J. F. F. Mendes

By the use of extensive numerical simulations we show that the nearest-neighbor energy level spacing distribution $P(s)$ and the entropic eigenfunction localization length of the adjacency matrices of Erd\H{o}s-R\'enyi (ER) {\it fully}…

Disordered Systems and Neural Networks · Physics 2015-06-24 J. A. Mendez-Bermudez , A. Alcazar-Lopez , A. J. Martinez-Mendoza , Francisco A. Rodrigues , Thomas K. DM. Peron

The shape and the inverse participation ratio (IPR) of local spectral density (LSD) are studied for a generic isolated system of coupled quantum states, the Hamiltonian of which is represented by a band random matrix with the disordered…

Quantum Physics · Physics 2009-11-07 V. S. Starovoitov

We study fluctuations of the local density of states (LDOS) on a tree-like lattice with large branching number $m$. The average form of the local spectral function (at given value of the random potential in the observation point) shows a…

Disordered Systems and Neural Networks · Physics 2009-10-30 Alexander D. Mirlin , Yan V. Fyodorov

We study the effects of spatial constraints on the structural properties of networks embedded in one or two dimensional space. When nodes are embedded in space, they have a well defined Euclidean distance $r$ between any pair. We assume…

Physics and Society · Physics 2009-11-13 Kosmas Kosmidis , Shlomo Havlin , Armin Bunde

We study spatial networks constructed by randomly placing nodes on a manifold and joining two nodes with an edge whenever their distance is less than a certain cutoff. We derive the general expression for the connectivity distribution of…

Disordered Systems and Neural Networks · Physics 2009-11-10 Carl Herrmann , Marc Barthelemy , Paolo Provero

The simplest null models for networks, used to distinguish significant features of a particular network from {\it a priori} expected features, are random ensembles with the degree sequence fixed by the specific network of interest. These…

Statistical Mechanics · Physics 2009-11-11 Jacob G. Foster , David V. Foster , Peter Grassberger , Maya Paczuski

Proximity networks are time-varying graphs representing the closeness among humans moving in a physical space. Their properties have been extensively studied in the past decade as they critically affect the behavior of spreading phenomena…

Physics and Society · Physics 2019-11-28 Fragkiskos Papadopoulos , Marco Antonio Rodríguez Flores

Approaches from statistical physics are applied to investigate the structure of network models whose growth rules mimic aspects of the evolution of the world-wide web. We first determine the degree distribution of a growing network in which…

Networking and Internet Architecture · Computer Science 2021-08-23 P. L. Krapivsky , S. Redner

We study statistical properties of a class of band random matrices which naturally appears in systems of interacting particles. The local spectral density is shown to follow the Breit-Wigner distribution in both localized and delocalized…

Condensed Matter · Physics 2009-10-28 Ph. Jacquod , D. L. Shepelyansky

A generalization of Brillouin-Wigner perturbation theory is applied numerically to the Wigner Band Random Matrix model. The perturbation theory tells that a perturbed energy eigenstate can be divided into a perturbative part and a…

Condensed Matter · Physics 2007-05-23 Wen-ge Wang

We discuss a non-equilibrium statistical system on a graph or network. Identical particles are injected, interact with each other, traverse, and leave the graph in a stochastic manner described in terms of Poisson rates, possibly dependent…

Statistical Mechanics · Physics 2015-05-19 V. Y. Chernyak , M. Chertkov , N. A. Sinitsyn

We study the spectral statistics and wave-function properties of a one-dimensional quantum system subject to a Cantor-type fractal potential. By analyzing the nearest-neighbor level spacings, inverse participation ratio (IPR), and the…

Disordered Systems and Neural Networks · Physics 2026-01-14 F. Iwase

In the last 15 years, statistical physics has been a very successful framework to model complex networks. On the theoretical side, this approach has brought novel insights into a variety of physical phenomena, such as self-organisation,…

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