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In the paper, we present an incremental approach in the construction of scale free networks with hidden variables. The work arises from the necessity to generate that type of networks with a given number of links instead of obtaining a…

Disordered Systems and Neural Networks · Physics 2021-06-10 Fabio Vanni

We study two variants of the well-known orthogonal drawing model: (i) the smooth orthogonal, and (ii) the octilinear. Both models form an extension of the orthogonal, by supporting one additional type of edge segments (circular arcs and…

Data Structures and Algorithms · Computer Science 2017-08-31 Michael A. Bekos , Henry Förster , Michael Kaufmann

For $\alpha \in (1,2]$, the $\alpha$-stable graph arises as the universal scaling limit of critical random graphs with i.i.d. degrees having a given $\alpha$-dependent power-law tail behavior. It consists of a sequence of compact measured…

Probability · Mathematics 2020-07-09 Christina Goldschmidt , Bénédicte Haas , Delphin Sénizergues

Finding the reduced-dimensional structure is critical to understanding complex networks. Existing approaches such as spectral clustering are applicable only when the full network is explicitly observed. In this paper, we focus on the online…

Machine Learning · Computer Science 2017-12-13 Lin F. Yang , Vladimir Braverman , Tuo Zhao , Mengdi Wang

Many empirical networks are intrinsically polyadic, with interactions occurring within groups of agents of arbitrary size. There are, however, few flexible null models that can support statistical inference for such polyadic networks. We…

Probability · Mathematics 2019-12-17 Philip S. Chodrow

Understanding the process by which the individuals of a society make up their minds and reach opinions about different issues can be of fundamental importance. In this work we propose an idealized model for competitive cluster growth in…

Disordered Systems and Neural Networks · Physics 2009-11-11 Andre A. Moreira , Demetrius R. Paula , Raimundo N. Costa Filho , Jose S. Andrade

Hierarchical networks are attracting a renewal interest for modelling the organization of a number of biological systems and for tackling the complexity of statistical mechanical models beyond mean-field limitations. Here we consider the…

Disordered Systems and Neural Networks · Physics 2016-01-26 Elena Agliari , Adriano Barra , Andrea Galluzzi , Francesco Guerra , Daniele Tantari , Flavia Tavani

Conventionally, pairwise relationships between nodes are considered to be the fundamental building blocks of complex networks. However, over the last decade the overabundance of certain sub-network patterns, so called motifs, has attracted…

Physics and Society · Physics 2015-01-28 Marco Winkler , Joerg Reichardt

What is the underlying mechanism leading to power-law degree distributions of many natural and artificial networks is still at issue. We consider that scale-free networks emerges from self-organizing process, and such a evolving model is…

Statistical Mechanics · Physics 2007-05-23 Gang Yan , Tao Zhou , Ying-Di Jin , Zhong-Qian Fu

Network models with latent geometry have been used successfully in many applications in network science and other disciplines, yet it is usually impossible to tell if a given real network is geometric, meaning if it is a typical element in…

Statistical Mechanics · Physics 2016-05-23 Dmitri Krioukov

Background: Recent models of genome-proteome evolution have shown that some of the key traits displayed by the global structure of cellular networks might be a natural result of a duplication-diversification (DD) process. One of the…

Genomics · Quantitative Biology 2007-05-23 Ricard V. Sole , Pau Fernandez

One explanation for the impressive recent boom in network theory might be that it provides a promising tool for an understanding of complex systems. Network theory is mainly focusing on discrete large-scale topological structures rather…

Statistical Mechanics · Physics 2015-06-25 Stefan Thurner

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

Clustering is well-known to play a prominent role in the description and understanding of complex networks, and a large spectrum of tools and ideas have been introduced to this end. In particular, it has been recognized that the abundance…

Disordered Systems and Neural Networks · Physics 2009-11-10 Danilo Sergi

We construct a polygonal spiral by arranging a sequence of regular $n$-gons such that each $n$-gon shares a specified side and vertex with the $(n+1)$-gon in the construction. By offering flexibility for determining the size of each $n$-gon…

Metric Geometry · Mathematics 2024-04-16 Kyle Fridberg

Real complex systems are not rigidly structured; no clear rules or blueprints exist for their construction. Yet, amidst their apparent randomness, complex structural properties universally emerge. We propose that an important class of…

Looking to overcome the limitations of traditional networks, the network science community has lately given much attention to the so-called higher-order networks, where group interactions are modeled alongside pairwise ones. While degree…

Physics and Society · Physics 2022-07-11 Demival Vasques Filho

Let $\mathscr{G}$ be the class of plane graphs without triangles normally adjacent to $8^{-}$-cycles, without $4$-cycles normally adjacent to $6^{-}$-cycles, and without normally adjacent $5$-cycles. In this paper, it is shown that every…

Combinatorics · Mathematics 2022-06-13 Fangyao Lu , Mengjiao Rao , Qianqian Wang , Tao Wang

There is a pressing need for a description of complex systems that includes considerations of the underlying network of interactions, for a diverse range of biological, technological and other networks. In this work relationships between…

Disordered Systems and Neural Networks · Physics 2007-05-23 Samantha Jenkins , Steven R. Kirk

A construction of Alon yields a sequence of highly pseudorandom triangle-free graphs with edge density significantly higher than one might expect from comparison with random graphs. We give an alternative construction for such graphs.

Combinatorics · Mathematics 2016-09-21 David Conlon
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