  Natural swimmers rely for their survival on sensors that gather information
from the environment and guide their actions. The spatial organization of these
sensors, such as the visual fish system and lateral line, suggests evolutionary
selection, but their optimality remains an open question. Here, we identify
sensor configurations that enable swimmers to maximize the information gathered
from their surrounding flow field. We examine two-dimensional, self-propelled
and stationary swimmers that are exposed to disturbances generated by
oscillating, rotating and D-shaped cylinders. We combine simulations of the
Navier-Stokes equations with Bayesian experimental design to determine the
optimal arrangements of shear and pressure sensors that best identify the
locations of the disturbance-generating sources. We find a marked tendency for
shear stress sensors to be located in the head and the tail of the swimmer,
while they are absent from the midsection. In turn, we find a high density of
pressure sensors in the head along with a uniform distribution along the entire
body. The resulting optimal sensor arrangements resemble neuromast
distributions observed in fish and provide evidence for optimality in sensor
distribution for natural swimmers.
