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Related Experiment Video

Updated: Jun 18, 2026

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0

Published on: June 5, 2017

Nonlinear q-voter model.

Claudio Castellano¹, Miguel A Muñoz, Romualdo Pastor-Satorras

¹SMC, INFM-CNR and Dipartimento di Fisica, Sapienza Università di Roma, Ple Aldo Moro 2, I-00185 Roma, Italy.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|November 13, 2009

Summary

This summary is machine-generated.

The q-voter model, a new opinion dynamics model, shows distinct phases and transitions. In mean field, it can exhibit unique or multiple transitions, with one scenario being specific to mean-field conditions.

Related Experiment Videos

Last Updated: Jun 18, 2026

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0

Published on: June 5, 2017

Area of Science:

Statistical Physics
Complex Systems
Sociophysics

Background:

The voter model is a fundamental tool for studying opinion dynamics.
Understanding phase transitions in systems with absorbing states is crucial.

Purpose of the Study:

Introduce and analyze the q-voter model, a nonlinear variant of the voter model.
Investigate opinion dynamics and phase transitions in a mean-field setting.

Main Methods:

Analytical solution using backward Fokker-Planck formalism and scaling arguments.
Analysis via a Langevin equation for Z2-symmetric absorbing states.
Derivation of Langevin equation coefficients from microscopic probabilities.

Main Results:

The q-voter model exhibits distinct disordered (high epsilon) and ordered (low epsilon) phases in mean field.
Three distinct pathways for phase transitions were identified: a single generalized-voter-like transition, two consecutive transitions (Ising-like and directed-percolation-like), or a novel scenario with an intermediate regime.
The third scenario, characterized by emergent ordering dynamics, is specific to mean-field and is suppressed by fluctuations in extended systems.

Conclusions:

The q-voter model provides a rich framework for studying complex opinion dynamics and phase transitions.
The identified transition scenarios offer new insights into the behavior of systems with absorbing states.
Mean-field analysis reveals unique phenomena that may not be present in spatially extended systems.