Exit probability in a one-dimensional nonlinear q-voter model

TL;DR

This paper derives an exact analytical formula for the exit probability in a one-dimensional nonlinear q-voter model, confirming its accuracy through simulations and exploring why mean field theory is exact in this context.

Contribution

It provides the first exact formula for the exit probability in the 1D nonlinear q-voter model and investigates the reasons behind the mean field approach's accuracy.

Findings

Analytical formula for exit probability matches simulations

Mean field approach is exact in this 1D nonlinear q-voter model

Finite size effects and initial conditions do not affect the formula's accuracy

Abstract

We formulate and investigate the nonlinear $q$-voter model (which as special cases includes the linear voter and the Sznajd model) on a one dimensional lattice. We derive analytical formula for the exit probability and show that it agrees perfectly with Monte Carlo simulations. The puzzle, that we deal with here, may be contained in a simple question: "Why the mean field approach gives the exact formula for the exit probability in the one-dimensional nonlinear $q$-voter model?". To answer this question we test several hypothesis proposed recently for the Sznajd model, including the finite size effects, the influence of the range of interactions and the importance of the initial step of the evolution. On the one hand, our work is part of a trend of the current debate on the form of the exit probability in the one-dimensional Sznajd model but on the other hand, it concerns the much broader problem of nonlinear $q$-voter model.