The noisy voter model with general initial conditions
Patrizio Caddeo, Eyal Lubetzky

TL;DR
This paper investigates the mixing times and cutoff phenomena of the noisy voter model with multiple states on various graphs, confirming conjectures about optimal initial conditions and providing explicit cutoff criteria based on autocorrelation.
Contribution
It establishes a general cutoff criterion for the noisy voter model on arbitrary graphs and confirms conjectures about fastest initial conditions in specific cases.
Findings
The noisy voter model exhibits cutoff at a time depending on initial autocorrelation.
Alternating initial states are fastest for the 1D Ising model on cyclic graphs.
Checkerboard and rainbow initial conditions are fastest in higher dimensions and for multiple states.
Abstract
We study the noisy voter model with states and noise probability on arbitrary bounded-degree -vertex graphs with subexponential growth of balls (e.g., finite subsets of ). Cox, Peres and Steif (2016) showed for the binary case (and a wider class of chains) that, when starting from a worst-case initial state, this Markov chain has total variation cutoff at . The second author and Sly (2021) analyzed faster initial conditions for Glauber dynamics for the 1D Ising model, which is the noisy voter for and . They showed that the ``alternating'' initial state is the fastest one if , and conjectured that this holds for all values of the noise . Here we show that for every graph as above and all and initial states , the noisy voter model…
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Taxonomy
TopicsGame Theory and Voting Systems · Opinion Dynamics and Social Influence · Spectral Theory in Mathematical Physics
