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We study the growth of random networks under a constraint that the diameter, defined as the average shortest path length between all nodes, remains approximately constant. We show that if the graph maintains the form of its degree…

Statistical Mechanics · Physics 2007-05-23 Rajan M. Lukose , Lada A. Adamic

Statistical field theory methods have been very successful with a number of random graph and random matrix problems, but it is challenging to apply these methods to graphs with prescribed degree sequences due to the extensive number of…

Statistical Mechanics · Physics 2025-05-20 Pawat Akara-pipattana , Oleg Evnin

In the classical Erd\"os-R\'enyi random graph G(n,p) there are n vertices and each of the possible edges is independently present with probability p. The random graph G(n,p) is homogeneous in the sense that all vertices have the same…

Combinatorics · Mathematics 2016-02-10 Mihyun Kang , Angelica Pachón , Pablo M. Rodriguez

A bridge in a graph is an edge whose removal disconnects the graph and increases the number of connected components. We calculate the fraction of bridges in a wide range of real-world networks and their randomized counterparts. We find that…

Physics and Society · Physics 2018-01-24 Ang-Kun Wu , Liang Tian , Yang-Yu Liu

The study of networks has received increased attention recently not only from the social sciences and statistics but also from physicists, computer scientists and mathematicians. One of the principal problem in networks is community…

Machine Learning · Statistics 2014-01-27 Sharmodeep Bhattacharyya , Peter J. Bickel

Discovering low-dimensional structure in real-world networks requires a suitable null model that defines the absence of meaningful structure. Here we introduce a spectral approach for detecting a network's low-dimensional structure, and the…

Social and Information Networks · Computer Science 2021-05-24 Mark D. Humphries , Javier A. Caballero , Mat Evans , Silvia Maggi , Abhinav Singh

Quantum graphs and their experimental counterparts, microwave networks, are ideally suited to study the spectral statistics of chaotic systems. The graph spectrum is obtained from the zeros of a secular determinant derived from energy and…

Mesoscale and Nanoscale Physics · Physics 2021-10-27 Tobias Hofmann , Junjie Lu , Ulrich Kuhl , Hans-Jürgen Stöckmann

Large-scale human social network structure is typically inferred from digital trace samples of online social media platforms or mobile communication data. Instead, here we investigate the social network structure of a complete population,…

Physics and Society · Physics 2022-11-29 Eszter Bokányi , Eelke M. Heemskerk , Frank W. Takes

We study numerically and analytically the spectrum of incidence matrices of random labeled graphs on N vertices : any pair of vertices is connected by an edge with probability p. We give two algorithms to compute the moments of the…

Statistical Mechanics · Physics 2015-06-24 M. Bauer , O. Golinelli

We study the spectrum of a random multigraph with a degree sequence ${\bf D}_n=(D_i)_{i=1}^n$ and average degree $1 \ll \omega_n \ll n$, generated by the configuration model, and also the spectrum of the analogous random simple graph. We…

Probability · Mathematics 2020-05-15 Amir Dembo , Eyal Lubetzky , Yumeng Zhang

Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical…

In this paper we generalize the concept of random networks to describe networks with non trivial features by a statistical mechanics approach. This framework is able to describe ensembles of undirected, directed as well as weighted…

Disordered Systems and Neural Networks · Physics 2009-11-13 Ginestra Bianconi

We give sufficient conditions under which a random graph with a specified degree sequence is symmetric or asymmetric. In the case of bounded degree sequences, our characterisation captures the phase transition of the symmetry of the random…

Combinatorics · Mathematics 2020-04-07 Lochlan Brick , Pu Gao , Angus Southwell

Randomized network ensembles are the null models of real networks and are extensivelly used to compare a real system to a null hypothesis. In this paper we study network ensembles with the same degree distribution, the same…

Disordered Systems and Neural Networks · Physics 2009-11-13 Ginestra Bianconi

We consider the number of crossings in a graph which is embedded randomly on a convex set of points. We give an estimate to the normal distribution in Kolmogorov distance which implies a convergence rate of order $n^{-1/2}$ for various…

Combinatorics · Mathematics 2022-08-26 Santiago Arenas-Velilla , Octavio Arizmendi

The structure of many real networks is not locally tree-like and hence, network analysis fails to characterise their bond percolation properties. In a recent paper [P. Mann, V. A. Smith, J. B. O. Mitchell, and S. Dobson, Percolation in…

Physics and Society · Physics 2021-01-27 Peter Mann , V. Anne Smith , John B. O. Mitchell , Simon Dobson

In this paper, we analyze the limiting spectral distribution of the adjacency matrix of a random graph ensemble, proposed by Chung and Lu, in which a given expected degree sequence $\overline{w}_n^{^{T}} = (w^{(n)}_1,\ldots,w^{(n)}_n)$ is…

Statistics Theory · Mathematics 2017-03-28 Victor M. Preciado , M. Amin Rahimian

The scaled standard Wigner matrix (symmetric with mean zero, variance one i.i.d. entries), and its limiting eigenvalue distribution, namely the semi-circular distribution, has attracted much attention. The $2k$th moment of the limit equals…

Probability · Mathematics 2021-03-18 Arup Bose , Koushik Saha , Arusharka Sen , Priyanka Sen

Network structures, consisting of nodes and edges, have applications in almost all subjects. A set of nodes is called a community if the nodes have strong interrelations. Industries (including cell phone carriers and online social media…

Social and Information Networks · Computer Science 2019-02-13 Haoye Lu , Amiya Nayak

We present a general method for obtaining the spectra of large graphs with short cycles using ideas from statistical mechanics of disordered systems. This approach leads to an algorithm that determines the spectra of graphs up to a high…

Disordered Systems and Neural Networks · Physics 2023-01-12 D. Bollé , F. L. Metz , I. Neri
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