Critical phenomena in a two-dimensional ferrimagnetic system: Monte Carlo and Mean-Field Analysis

2019 ◽  
Vol 531 ◽  
pp. 121738 ◽  
Author(s):  
M. Karimou ◽  
N. De La Espriella
2022 ◽  
Vol 2022 (1) ◽  
pp. 013402
Author(s):  
Xiang Li ◽  
Mauro Mobilia ◽  
Alastair M Rucklidge ◽  
R K P Zia

Abstract We investigate the long-time properties of a dynamic, out-of-equilibrium network of individuals holding one of two opinions in a population consisting of two communities of different sizes. Here, while the agents’ opinions are fixed, they have a preferred degree which leads them to endlessly create and delete links. Our evolving network is shaped by homophily/heterophily, a form of social interaction by which individuals tend to establish links with others having similar/dissimilar opinions. Using Monte Carlo simulations and a detailed mean-field analysis, we investigate how the sizes of the communities and the degree of homophily/heterophily affect the network structure. In particular, we show that when the network is subject to enough heterophily, an ‘overwhelming transition’ occurs: individuals of the smaller community are overwhelmed by links from the larger group, and their mean degree greatly exceeds the preferred degree. This and related phenomena are characterized by the network’s total and joint degree distributions, as well as the fraction of links across both communities and that of agents having fewer edges than the preferred degree. We use our mean-field theory to discuss the network’s polarization when the group sizes and level of homophily vary.


1997 ◽  
Vol 55 (5) ◽  
pp. 5225-5233 ◽  
Author(s):  
Kevin E. Bassler ◽  
Dana A. Browne

1998 ◽  
Vol 09 (07) ◽  
pp. 1107-1119 ◽  
Author(s):  
Eric Bonabeau ◽  
Florian Hénaux

A Monte Carlo algorithm for partitioning graphs is presented. The algorithm is based on the self-organizing map, an unsupervised, competitive neural network. A mean-field analysis suggests that the complexity of the algorithm is at most is on the order of O(n3/|E|), where n is the number of vertices of the graph, and |E| the number of edges. This prediction is tested on a class of random graphs. Scaling laws that deviate from the mean-field prediction are obtained. Although the origin of these scaling laws is unclear, their consequences are discussed.


1977 ◽  
Vol 32 (11) ◽  
pp. 1320-1322 ◽  
Author(s):  
S. Romano

Abstract Monte-Carlo calculations were carried out on a system consisting of 256 point-dipoles, whose centres are fixed in a two-dimensional square lattice with the usual boundary con­dition; the Epstein-Ewald-Kornfeld algorithm was used in evaluating the electrostatic energy. No evidence of a first-order phase transition was found, and the results suggest there might be a second-order one. Additional calculations were carrierd out using the mean-field theory, which was found to overestimate the transition temperature by about a factor two.


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