Majority vote model with ancillary noise in complex networks
J. M. Encinas, Hanshuang Chen, Marcelo M. de Oliveira, C. E. Fiore

TL;DR
This paper studies a noisy majority-vote model on various complex networks, showing that the phase transition remains continuous and identifying how critical points depend on network structure and connectivity.
Contribution
It generalizes the noisy majority-vote model to arbitrary networks and analyzes its critical behavior through mean-field and numerical methods.
Findings
Phase transition remains continuous across different networks.
Critical points increase with network connectivity.
Critical exponents vary between network types.
Abstract
We analyze the properties of the majority-vote (MV) model with an additional noise in which a local spin can be changed independently of its neighborhood. In the standard MV, one of the simplest nonequilibrium systems exhibiting an order-disorder phase transition, spins are aligned with their local majority with probability , and with complementary probability , the majority rule is not followed. In the noisy MV (NMV), a random spin flip is succeeded with probability (with complementary the usual MV rule is accomplished). Such extra ingredient was considered by Vieira and Crokidakis [Physica A {\bf 450}, 30 (2016)] for the square lattice. Here, we generalize the NMV for arbitrary networks, including homogeneous [random regular (RR) and Erd\"os Renyi (ER)] and heterogeneous [Barabasi-Albert (BA)] structures, through mean-field calculations and numerical simulations.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
