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相关论文: Sandpile model on Scale Free Networks with prefere…

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Avalanche dynamics is an indispensable feature of complex systems. Here we study the self-organized critical dynamics of avalanches on scale-free networks with degree exponent $\gamma$ through the Bak-Tang-Wiesenfeld (BTW) sandpile model.…

统计力学 · 物理学 2007-05-23 D. -S. Lee , K. -I. Goh , B. Kahng , D. Kim

Complex networks in different areas exhibit degree distributions with heavy upper tail. A preferential attachment mechanism in a growth process produces a graph with this feature. We herein investigate a variant of the simple preferential…

概率论 · 数学 2018-04-18 Angelica Pachon , Laura Sacerdote , Shuyi Yang

We show that not only preferential attachment but also preferential depletion leads to scale-free networks. The resulting degree distribution exponents is typically less than two (5/3) as opposed to the case of the growth models studied…

物理与社会 · 物理学 2015-05-27 Christian M. Schneider , Lucilla de Arcangelis , Hans J. Herrmann

Using a steady state process of node duplication and deletion we produce networks with 1/k scale-free degree distributions in the limit of vanishing connectance. This occurs even though there is no growth involved and inherent preferential…

统计力学 · 物理学 2007-05-23 Simon Laird , Henrik Jeldtoft Jensen

It is commonly believed that real networks are scale-free and fraction of nodes $P(k)$ with degree $k$ satisfies the power law $P(k) \propto k^{-\gamma} \text{ for } k > k_{min} > 0$. Preferential attachment is the mechanism that has been…

数据结构与算法 · 计算机科学 2023-06-22 Raheel Anwar , Muhammad Irfan Yousuf , Muhammad Abid

A dissipative stochastic sandpile model is constructed and studied on small world networks in one and two dimensions with different shortcut densities $\phi$, where $\phi=0$ represents regular lattice and $\phi=1$ represents random network.…

统计力学 · 物理学 2022-02-23 Himangsu Bhaumik , S. B. Santra

We introduce the sandpile model on multiplex networks with more than one type of edge and investigate its scaling and dynamical behaviors. We find that the introduction of multiplexity does not alter the scaling behavior of avalanche…

物理与社会 · 物理学 2012-03-07 Kyu-Min Lee , K. -I. Goh , I. -M. Kim

We investigate a growing network model that combines preferential and uniform attachment with two distinct mechanisms of edge deletion. In addition to the usual uniform probability edge deletion, we introduce a novel node-based rule in…

适应与自组织系统 · 物理学 2026-02-24 Everton R. Constantino , Alberto Saa

We investigate sandpile models where the updating of unstable columns is done according to a stochastic rule. We examine the effect of introducing nonlocal relaxation mechanisms. We find that the models self-organize into critical states…

统计力学 · 物理学 2009-10-30 L. A. N. Amaral , K. B. Lauritsen

We study the critical properties of the Bak-Sneppen coevolution model on scale-free networks by Monte Carlo method. We report the distribution of the avalanche size and fractal activity through the branching process. We observe that the…

统计力学 · 物理学 2007-05-23 Kyoung Eun Lee , Byoung Hee Hong , Jae Woo Lee

We investigate the avalanche dynamics of the Bak-Tang-Wiesenfeld (BTW) sandpile model on scale-free (SF) networks, where threshold height of each node is distributed heterogeneously, given as its own degree. We find that the avalanche size…

统计力学 · 物理学 2007-05-23 K. -I. Goh , D. -S. Lee , B. Kahng , D. Kim

A dissipative stochastic sandpile model is constructed on one and two dimensional small-world networks with different shortcut densities $\phi$ where $\phi=0$ and $1$ represent a regular lattice and a random network respectively. In the…

统计力学 · 物理学 2017-10-25 Himangsu Bhaumik , S. B. Santra

A dissipative sandpile model (DSM) is constructed and studied on small world networks (SWN). SWNs are generated adding extra links between two arbitrary sites of a two dimensional square lattice with different shortcut densities $\phi$.…

统计力学 · 物理学 2014-01-23 Himangsu Bhaumik , S. B. Santra

We examine probability distribution for avalanche sizes observed in self-organized critical systems. While a power-law distribution with a cutoff because of finite system size is typical behavior, a systematic investigation reveals that it…

统计力学 · 物理学 2022-08-09 Avinash Chand Yadav , Abdul Quadir , Haider Hasan Jafri

Rotational constraint representing a local external bias generally has non-trivial effect on the critical behavior of lattice statistical models in equilibrium critical phenomena. In order to study the effect of rotational bias in a out of…

软凝聚态物质 · 物理学 2009-11-13 S. B. Santra , S. Ranjita Chanu , D. Deb

Many real-world scale-free networks, such as neural networks and online communication networks, consist of a fixed number of nodes but exhibit dynamic edge fluctuations. However, traditional models frequently overlook scenarios where the…

社会与信息网络 · 计算机科学 2026-04-02 Yichao Yao , Minyu Feng , Matjaž Perc , Jürgen Kurths

We propose and study a model of scale-free growing networks that gives a degree distribution dominated by a power-law behavior with a model-dependent, hence tunable, exponent. The model represents a hybrid of the growing networks based on…

无序系统与神经网络 · 物理学 2009-11-10 H. Y. Lee , H. Y. Chan , P. M. Hui

In this paper, we present a simple model of scale-free networks that incorporates both preferential & random attachment and anti-preferential & random deletion at each time step. We derive the degree distribution analytically and show that…

数据分析、统计与概率 · 物理学 2007-05-23 Dinghua Shi , Xiang Zhu , Liming Liu

Deterministic sandpile models are studied on a cost optimized Barab\'asi-Albert (BA) scale-free network whose nodes are the sites of a square lattice. For the optimized BA network, the sandpile model has the same critical behaviour as the…

统计力学 · 物理学 2009-11-11 R. Karmakar , S. S. Manna

We introduce a sandpile model where, at each unstable site, all grains are transferred randomly to downstream neighbors. The model is local and conservative, but not Abelian. This does not appear to change the universality class for the…

统计力学 · 物理学 2009-11-07 David Hughes , Maya Paczuski
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