AI Article Synopsis
- The study focuses on the q-voter model with stochastic noise in complex networks, using pair approximation to mathematically describe its behavior.
- A formula for the critical point is derived, and the findings are supported by Monte Carlo simulations, showing strong agreement in networks with weak clustering and high average degree.
- This is the first application of this approach to nonlinear voter dynamics with noise, establishing that the pair approximation prediction aligns with existing solutions on fully connected networks in the limiting case.
Article Abstract
We investigate the q-voter model with stochastic noise arising from independence on complex networks. Using the pair approximation, we provide a comprehensive, mathematical description of its behavior and derive a formula for the critical point. The analytical results are validated by carrying out Monte Carlo experiments. The pair approximation prediction exhibits substantial agreement with simulations, especially for networks with weak clustering and large average degree. Nonetheless, for the average degree close to q, some discrepancies originate. It is the first time we are aware of that the presented approach has been applied to the nonlinear voter dynamics with noise. Up till now, the analytical results have been obtained only for a complete graph. We show that in the limiting case the prediction of pair approximation coincides with the known solution on a fully connected network.
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| http://dx.doi.org/10.1103/PhysRevE.95.012307 | DOI Listing |
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