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相关论文: Explosive Percolation is Continuous, but with Unus…

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Explosive percolation in the Achlioptas process, which has attracted much research attention, is known to exhibit a rich variety of critical phenomena that are anomalous from the perspective of continuous phase transitions. Hereby, we show…

统计力学 · 物理学 2023-04-06 Ming Li , Junfeng Wang , Youjin Deng

Percolation is one of the most studied processes in statistical physics. A recent paper by Achlioptas et al. [Science 323, 1453 (2009)] has shown that the percolation transition, which is usually continuous, becomes discontinuous…

物理与社会 · 物理学 2010-03-24 Filippo Radicchi , Santo Fortunato

Networks are ubiquitous in diverse real-world systems. Many empirical networks grow as the number of nodes increases with time. Percolation transitions in growing random networks can be of infinite order. However, when the growth of large…

物理与社会 · 物理学 2021-04-28 Soo Min Oh , Seung-Woo Son , Byungnam Kahng

In this paper we review the recent advances on explosive percolation, a very sharp phase transition first observed by Achlioptas et al. (Science, 2009). There a simple model was proposed, which changed slightly the classical percolation…

统计力学 · 物理学 2015-01-28 Nikolaos Bastas , Paraskevas Giazitzidis , Michael Maragakis , Kosmas Kosmidis

In this Letter, we show that the explosive percolation is a novel continuous phase transition. The order-parameter-distribution histogram at the percolation threshold is studied in Erd\H{o}s-R\'{e}nyi networks, scale-free networks, and…

无序系统与神经网络 · 物理学 2012-02-22 Liang Tian , Da-Ning Shi

It is widely believed that certain simple modifications of the random graph process lead to discontinuous phase transitions. In particular, starting with the empty graph on $n$ vertices, suppose that at each step two pairs of vertices are…

概率论 · 数学 2012-08-22 Oliver Riordan , Lutz Warnke

The explosive percolation problem on the complete graph is investigated via extensive numerical simulations. We obtain the cluster-size distribution at the moment when the cluster size heterogeneity becomes maximum. The distribution is…

统计力学 · 物理学 2015-05-27 Hyun Keun Lee , Beom Jun Kim , Hyunggyu Park

In the usual Achlioptas processes the smallest clusters of a few randomly chosen ones are selected to merge together at each step. The resulting aggregation process leads to the delayed birth of a giant cluster and the so-called explosive…

无序系统与神经网络 · 物理学 2015-04-27 R. A. da Costa , S. N. Dorogovtsev , A. V. Goltsev , J. F. F. Mendes

We study the percolation transition in growing networks under an Achlioptas process (AP). At each time step, a node is added in the network and, with the probability $\delta$, a link is formed between two nodes chosen by an AP. We find that…

统计力学 · 物理学 2013-08-07 Su Do Yi , Woo Seong Jo , Beom Jun Kim , Seung-Woo Son

The Achlioptas process, which suppresses the aggregation of large-sized clusters, can exhibit an explosive percolation (EP) where the order parameter emerges abruptly yet continuously in the thermodynamic limit. It is known that EP is…

统计力学 · 物理学 2024-08-19 Young Sul Cho

In a new type of percolation phase transition, which was observed in a set of non-equilibrium models, each new connection between vertices is chosen from a number of possibilities by an Achlioptas-like algorithm. This causes preferential…

无序系统与神经网络 · 物理学 2015-06-18 R. A. da Costa , S. N. Dorogovtsev , A. V. Goltsev , J. F. F. Mendes

Explosive percolation in the Achlioptas process has recently attracted much research attention. From extensive simulations in an event-based ensemble, we find that, in dimensions from $2$ to $6$ and on random graphs, the Achlioptas…

统计力学 · 物理学 2022-08-23 Ming Li , Junfeng Wang , Youjin Deng

The growth of two-dimensional lattice bond percolation clusters through a cooperative Achlioptas-type of process, where the choice of which bond to occupy next depends upon the masses of the clusters it connects, is shown to go through an…

无序系统与神经网络 · 物理学 2009-07-03 Robert M. Ziff

The basic notion of percolation in physics assumes the emergence of a giant connected (percolation) cluster in a large disordered system when the density of connections exceeds some critical value. Until recently, the percolation phase…

无序系统与神经网络 · 物理学 2015-05-19 R. A. da Costa , S. N. Dorogovtsev , A. V. Goltsev , J. F. F. Mendes

The finite-size scaling theory for continuous phase transition plays an important role in determining critical point and critical exponents from the size-dependent behaviors of quantities in the thermodynamic limit. For percolation phase…

统计力学 · 物理学 2017-10-10 Yong Zhu , Xiaosong Chen

The biased link occupation rule in the Achlioptas process (AP) discourages the large clusters to grow much ahead of others and encourages faster growth of clusters which lag behind. In this paper we propose a model where this tendency is…

无序系统与神经网络 · 物理学 2011-01-04 S. S. Manna , Arnab Chatterjee

The finite-size scaling (FSS) theory for continuous phase transitions has been useful in determining the critical behavior from the size dependent behaviors of thermodynamic quantities. When the phase transition is discontinuous, however,…

统计力学 · 物理学 2015-05-19 Y. S. Cho , S. -W. Kim , J. D. Noh , B. Kahng , D. Kim

Clusters generated by the product-rule growth model of Achlioptas, D'Souza, and Spencer on a two-dimensional square lattice are shown to obey qualitatively different scaling behavior than standard (random growth) percolation. The threshold…

无序系统与神经网络 · 物理学 2013-05-29 Robert M. Ziff

We study the percolation properties of the growing clusters model. In this model, a number of seeds placed on random locations on a lattice are allowed to grow with a constant velocity to form clusters. When two or more clusters eventually…

统计力学 · 物理学 2015-05-18 Nikolaos Tsakiris , Michail Maragakis , Kosmas Kosmidis , Panos Argyrakis

We show that only considering the largest cluster suffices to obtain a first-order percolation transition. As opposed to previous realizations of explosive percolation our models obtain Gaussian cluster distributions and compact clusters as…

统计力学 · 物理学 2010-07-15 N. A. M. Araújo , H. J. Herrmann
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