  The majority-vote (MV) model is one of the simplest nonequilibrium Ising-like
model that exhibits a continuous order-disorder phase transition at a critical
noise. In this paper, we present a quenched mean-field theory for the dynamics
of the MV model on networks. We analytically derive the critical noise on
arbitrary quenched unweighted networks, which is determined by the largest
eigenvalue of a modified network adjacency matrix. By performing extensive
Monte Carlo simulations on synthetic and real networks, we find that the
performance of the quenched mean-field theory is superior to a heterogeneous
mean-field theory proposed in a previous paper [Chen \emph{et al.}, Phys. Rev.
E 91, 022816 (2015)], especially for directed networks.
