  We study metastability and mixing time for a non-reversible probabilistic
cellular automaton. With a suitable choice of the parameters, we first show
that the stationary distribution is close in total variation to a low
temperature Ising model. Then we prove that both the mixing time and the time
to exit a metastable state grow polynomially in the size of the system, while
this growth is exponential in reversible dynamics. In this model,
non-reversibility, parallel updatings and a suitable choice of boundary
conditions combine to produce an efficient dynamical stability.
