  We introduce the affine OBDD model and show that zero-error affine OBDDs can
be exponentially narrower than bounded-error unitary and probabilistic OBDDs on
certain problems. Moreover, we show that Las Vegas unitary and probabilistic
OBDDs can be quadratically narrower than deterministic OBDDs. We also obtain
the same results by considering the automata versions of these models.
