Biswas–Chatterjee–Sen Model Defined on Solomon Networks in (1 ≤ <i>D</i> ≤ 6)-Dimensional Lattices

Biswas–Chatterjee–Sen Model Defined on Solomon Networks in (1 ≤ <i>D</i> ≤ 6)-Dimensional Lattices

The discrete version of the Biswas–Chatterjee–Sen model, defined on <i>D</i>-dimensional hypercubic Solomon networks, with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn>...

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Main Authors: Gessineide Sousa Oliveira, David Santana Alencar, Tayroni Alencar Alves, José Ferreira da Silva Neto, Gladstone Alencar Alves, Antônio Macedo-Filho, Ronan S. Ferreira, Francisco Welington Lima, João Antônio Plascak
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Entropy
Subjects:
nonequilibrium
phase transition
Monte Carlo simulations
Solomon networks
lower upper critical dimension
Online Access:https://www.mdpi.com/1099-4300/27/3/300
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Summary:The discrete version of the Biswas–Chatterjee–Sen model, defined on <i>D</i>-dimensional hypercubic Solomon networks, with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mo>≤</mo><mi>D</mi><mo>≤</mo><mn>6</mn></mrow></semantics></math></inline-formula>, has been studied by means of extensive Monte Carlo simulations. Thermodynamic-like variables have been computed as a function of the external noise probability. Finite-size scaling theory, applied to different network sizes, has been utilized in order to characterize the phase transition of the system in the thermodynamic limit. The results show that the model presents a phase transition of the second order for all considered dimensions. Despite the lower critical dimension being zero, this dynamical system seems not to have any upper critical dimension since the critical exponents change with <i>D</i> and go away from the expected mean-field values. Although larger networks could not be simulated because the number of sites drastically increases with the dimension <i>D</i>, the scaling regime has been achieved when computing the critical exponent ratios and the corresponding critical noise probability.
ISSN:1099-4300

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