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We propose a model for growing networks based on a finite memory of the nodes. The model shows stylized features of real-world networks: power law distribution of degree, linear preferential attachment of new links and a negative…

Condensed Matter · Physics 2009-11-07 Konstantin Klemm , Victor M. Eguiluz

In this paper, we analyze the behavior of the global clustering coefficient in scale free graphs. We are especially interested in the case of degree distribution with an infinite variance, since such degree distribution is usually observed…

Probability · Mathematics 2015-06-09 Liudmila Ostroumova Prokhorenkova , Egor Samosvat

Scale independence is a ubiquitous feature of complex systems which implies a highly skewed distribution of resources with no characteristic scale. Research has long focused on why systems as varied as protein networks, evolution and stock…

Physics and Society · Physics 2016-02-08 Laurent Hébert-Dufresne , Antoine Allard , Jean-Gabriel Young , Louis J. Dubé

Clusters appear in nature in a diversity of contexts, involving distances as long as the cosmological ones, and down to atoms and molecules and the very small nuclear size. They also appear in several other scenarios, in particular in…

Populations and Evolution · Quantitative Biology 2020-02-19 D. Bazeia , M. V. de Moraes , B. F. de Oliveira

The scaling properties of the cluster size distribution of a system of diffusing clusters is studied in terms of a simple kinetic mean field model. It is shown that a one parameter family of mathematically valid scaling solutions exists.…

Statistical Mechanics · Physics 2009-10-31 Daniel Kandel

We report on the construction of a granular network of particles to study the formation, evolution and statistical properties of clusters of particles developing at the vicinity of a liquid-solid-like phase transition within a vertically…

Statistical Mechanics · Physics 2023-12-25 Enrique Navarro , Claudio Falcón

The inclusion of a fragmentation mechanism in population balance equations introduces complex interactions that make the analytical or even computational treatment much more difficult than for the pure aggregation case. This is specially…

Disordered Systems and Neural Networks · Physics 2022-03-14 Arturo Berrones-Santos , Luis Benavides-Vázquez , Elisa Schaeffer , Javier Almaguer

We investigate a class of stochastic aggregation processes involving two types of clusters: active and passive. The mass distribution is obtained analytically for several aggregation rates. When the aggregation rate is constant, we find…

Statistical Mechanics · Physics 2007-05-23 P. L. Krapivsky , E. Ben-Naim

The applicability of agglomerative clustering, for inferring both hierarchical and flat clustering, is limited by its scalability. Existing scalable hierarchical clustering methods sacrifice quality for speed and often lead to over-merging…

Cohesive particles form agglomerates that are usually very porous. Their geometry, particularly their fractal dimension, depends on the agglomeration process (diffusion-limited or ballistic growth by adding single particles or…

Soft Condensed Matter · Physics 2023-12-07 Dietrich E. Wolf , Thorsten Pöschel

Scale invariance (fractality) is a prominent feature of the large-scale behavior of many stochastic systems. In this work, we construct an algorithm for the statistical identification of the Hurst distribution (in particular, the scaling…

Methodology · Statistics 2025-01-31 Patrice Abry , Gustavo Didier , Oliver Orejola , Herwig Wendt

We describe the topological structure and the underlying organization principles of the directories created by users of a computer cluster when storing his/her own files. We analyze degree distributions, average distance between files,…

Disordered Systems and Neural Networks · Physics 2011-06-16 Konstantin Klemm , Victor M. Eguiluz , Maxi San Miguel

A thorough discussion of the statistical ensemble of scale-free connected random tree graphs is presented. Methods borrowed from field theory are used to define the ensemble and to study analytically its properties. The ensemble is…

Statistical Mechanics · Physics 2009-11-07 Z. Burda , J. D. Correia , A. Krzywicki

We calculate the time-evolution of a discrete-time fragmentation process in which clusters of particles break up and reassemble and move stochastically with size-dependent rates. In the continuous-time limit the process turns into the…

Statistical Mechanics · Physics 2007-05-23 A. Rákos , G. M. Schütz

Probabilistic networks display a wide range of high average clustering coefficients independent of the number of nodes in the network. In particular, the local clustering coefficient decreases with the degree of the subtending node in a…

Physics and Society · Physics 2013-11-26 Vijay K Samalam

The distribution function of particles over clusters is proposed for a system of identical intersecting spheres, the centres of which are uniformly distributed in space. Consideration is based on the concept of the rank number of clusters,…

Statistical Mechanics · Physics 2023-02-01 Murat Kh. Khokonov , Azamat Kh. Khokonov

Groups of cells, including clusters of cancerous cells, multicellular organisms, and developing organs, may both grow and break apart. What physical factors control these fractures? In these processes, what sets the eventual size of…

Biological Physics · Physics 2026-04-03 Wei Wang , Brian A. Camley

Co-evolution exhibited by a network system, involving the intricate interplay between the dynamics of the network itself and the subsystems connected by it, is a key concept for understanding the self-organized, flexible nature of…

Physics and Society · Physics 2012-11-14 Takaaki Aoki , Toshio Aoyagi

We study the evolution of percolation with freezing. Specifically, we consider cluster formation via two competing processes: irreversible aggregation and freezing. We find that when the freezing rate exceeds a certain threshold, the…

Statistical Mechanics · Physics 2007-05-23 E. Ben-Naim , P. L. Krapivsky

We extend the standard scale-free network model to include a ``triad formation step''. We analyze the geometric properties of networks generated by this algorithm both analytically and by numerical calculations, and find that our model…

Disordered Systems and Neural Networks · Physics 2009-11-07 Petter Holme , Beom Jun Kim