Domain motion in the voter model with noise

We study the voter model with noise on one-dimensional chains using Monte Carlo simulations and finite-size scaling techniques. We observe that the system evolution toward consensus is deeply affected by the addition of noise, and that the time to reach complete ordering increases with the noise parameter q. In particular, the simulations show that the average domain size scales as xi similar to q(-1/2) whereas the magnetization scales with the number of nodes as m similar to N-1/2.