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Related papers: From regular to growing small-world networks

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The degree distribution, referred to as the delta-sequence of a network is studied. Using the non-normalized Lorenz curve, we apply a generalized form of the classical majorization partial order. Next, we introduce a new class of small…

General Mathematics · Mathematics 2024-03-28 Leo Egghe

Evolving network models under a dynamic growth rule which comprises the addition and deletion of nodes are investigated. By adding a node with a probability $P_a$ or deleting a node with the probability $P_d=1-P_a$ at each time step, where…

Physics and Society · Physics 2011-08-09 Ke Deng , Ke Hu , Yi Tang

In this article, we have employed Monte Carlo simulations to study the Ising model on a two-dimensional additive small-world network (A-SWN). The system model consists of a LxL square lattice where each site of the lattice is occupied for a…

Statistical Mechanics · Physics 2022-10-19 R. A. Dumer , M. Godoy

Adaptive networks are a novel class of dynamical networks whose topologies and states coevolve. Many real-world complex systems can be modeled as adaptive networks, including social networks, transportation networks, neural networks and…

Social and Information Networks · Computer Science 2017-05-29 Hiroki Sayama , Irene Pestov , Jeffrey Schmidt , Benjamin James Bush , Chun Wong , Junichi Yamanoi , Thilo Gross

We report on a detailed numerical study of the evolution of semilocal string networks, based on the largest and most accurate field theory simulations of these objects to date. We focus on the large-scale network properties, confirming…

High Energy Physics - Phenomenology · Physics 2014-03-24 A. Achúcarro , A. Avgoustidis , A. M. M. Leite , A. Lopez-Eiguren , C. J. A. P. Martins , A. S. Nunes , J. Urrestilla

The small-world property in the context of complex networks implies structural benefits to the processes taking place within a network, such as optimal information transmission and robustness. In this paper, we study a model network of…

Adaptation and Self-Organizing Systems · Physics 2015-08-03 Victor Hernandez-Urbina , J. Michael Herrmann

We study the evolution of domain wall networks appearing after phase transitions in the early Universe. They exhibit interesting dynamical scaling behaviour which is not yet well understood, and are also simple models for the more…

High Energy Physics - Phenomenology · Physics 2009-11-07 Theodore Garagounis , Mark Hindmarsh

This paper employs a weighted network approach to study the empirical properties of the web of trade relationships among world countries, and its evolution over time. We show that most countries are characterized by weak trade links; yet,…

Social and Information Networks · Computer Science 2018-03-21 Maddalena D'Anna , Alfredo Petrosino

Motivated by data on the evolution of the Internet and World Wide Web we consider scenarios of self-organization of the nonlinearly growing networks into free-scale structures. We find that the accelerating growth of the networks…

Statistical Mechanics · Physics 2009-10-31 S. N. Dorogovtsev , J. F. F. Mendes

We analyze the propagation of activity in a system of mobile automata. A number r L^d of elements move as random walkers on a lattice of dimension d, while with a small probability p they can jump to any empty site in the system. We show…

Condensed Matter · Physics 2009-11-07 Susanna C. Manrubia , Jordi Delgado , Bartolo Luque

We propose an approach based on analysis of cost-quality tradeoffs for comparison of efficiency of various algorithms for small-world network construction. A number of both known in the literature and original algorithms for complex…

Social and Information Networks · Computer Science 2014-02-18 A. Demichev , V. Ilyin , A. Kryukov , S. Polyakov

Recent years have seen a growing interest in the modeling and simulation of social networks to understand several social phenomena. Two important classes of networks, small world and scale free networks have gained a lot of research…

Social and Information Networks · Computer Science 2014-11-04 Mohammad Qasim Pasta , Zohaib Jan , Arnaud Sallaberry , Faraz Zaidi

Traditional random graph models of networks generate networks that are locally tree-like, meaning that all local neighborhoods take the form of trees. In this respect such models are highly unrealistic, most real networks having strongly…

Statistical Mechanics · Physics 2011-03-02 Brian Karrer , M. E. J. Newman

We present two different approaches to model power grids as interconnected networks of networks. Both models are derived from a model for spatially embedded mono-layer networks and are generalised to handle an arbitrary number of network…

Physics and Society · Physics 2017-01-25 Paul Schultz , Frank Hellmann , Jobst Heitzig , Jürgen Kurths

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

We consider random networks whose dynamics is described by a rate equation, with transition rates $w_{nm}$ that form a symmetric matrix. The long time evolution of the system is characterized by a diffusion coefficient $D$. In one dimension…

Statistical Mechanics · Physics 2012-12-04 Yaron de Leeuw , Doron Cohen

In this paper we present a model for the growth and evolution of Internet providers. The model reproduces the data observed for the Internet connection as probed by tracing routes from different computers. This problem represents a…

Disordered Systems and Neural Networks · Physics 2009-11-07 A. Capocci , G. Caldarelli , R. Marchetti , L. Pietronero

The Ising model in small-world networks generated from two- and three-dimensional regular lattices has been studied. Monte Carlo simulations were carried out to characterize the ferromagnetic transition appearing in these systems. In the…

Disordered Systems and Neural Networks · Physics 2009-11-07 Carlos P. Herrero

Most agent-based models include a social network that describes the structure of interactions within the artificial population. Because of the dramatic impact of this structure on the simulated dynamics, modelers create this network for it…

Physics and Society · Physics 2020-02-11 Samuel Thiriot

A generative recurrent neural network is quickly trained in an unsupervised manner to model popular reinforcement learning environments through compressed spatio-temporal representations. The world model's extracted features are fed into…

Machine Learning · Computer Science 2018-09-07 David Ha , Jürgen Schmidhuber