  The emergence of collective decision in swarms and their coordinated response
to complex environments underscore the central role played by social
transmission of information. Here, the different possible origins of
information flow bottlenecks are identified. Using a combination of network-,
control- and information-theoretic elements applied to a group of interacting
self-propelled particles, the effect of varying information capacity of the
signaling channel on dynamic collective behaviors is revealed. We find a
sufficient condition on the information data rate that guarantees the
effectiveness of swarming while also highlighting the profound connection with
the topology of the underlying interaction network. We also show that when
decreasing the data rate, the swarming behavior invariably vanishes following a
second-order phase transition irrespective of the intrinsic noise level. The
variations along the transition line are found to be in good agreement with
information-theoretic predictions.
