  The voter model is a toy model of consensus formation based on
nearest-neighbor interactions. A voter sits at each vertex in a hypercubic
lattice (of dimension $d$) and is in one of two possible opinion states. The
opinion state of each voter flips randomly, at a rate proportional to the
fraction of the nearest neighbors that disagree with the voter. If the voters
are initially independent and undecided, the model is known to lead to a
consensus if and only if $d\leq 2$. In this paper the model is subjected to
stochastic resetting: the voters revert independently to their initial opinion
according to a Poisson process of fixed intensity (the resetting rate). This
resetting prescription induces kinetic equations for the average opinion state
and for the two-point function of the model. For initial conditions consisting
of undecided voters except for one decided voter at the origin, the one-point
function evolves as the probability of presence of a diffusive random walker on
the lattice, whose position is stochastically reset to the origin. The
resetting prescription leads to a non-equilibrium steady state. For an initial
state consisting of independent undecided voters, the density of domain walls
in the steady state is expressed in closed form as a function of the resetting
rate. This function is differentiable at zero if and only if $d\geq 5$.
