  We investigate the fundamental limits of reliable communication over
multi-view channels, in which the channel output is comprised of a large number
of independent noisy views of a transmitted symbol. We consider first the
setting of multi-view discrete memoryless channels and then extend our results
to general multi-view channels (using multi-letter formulas). We argue that the
channel capacity and dispersion of such multi-view channels converge
exponentially fast in the number of views to the entropy and varentropy of the
input distribution, respectively. We identify the exact rate of convergence as
the smallest Chernoff information between two conditional distributions of the
output, conditioned on unequal inputs. For the special case of the deletion
channel, we compute upper bounds on this Chernoff information. Finally, we
present a new channel model we term the Poisson approximation channel -- of
possible independent interest -- whose capacity closely approximates the
capacity of the multi-view binary symmetric channel for any fixed number of
views.
