  We study an information-based mechanism of self-propulsion in noisy
environment. An information swimmer maintains directional motion by
periodically measuring its velocity and accordingly adjusting its friction
coefficient. Assuming that the measurement and adjustment are reversible and
hence cause no energy dissipation, an information swimmer may move without
external energy input. There is however no violation of the second law of
thermodynamics, because the information entropy stored in the memory of swimmer
increases monotonically. By optimizing its control parameters, the swimmer can
achieve a steady velocity that is comparable to the root-mean-square velocity
of an analogous Brownian particle. We also define a swimming efficiency in
terms of information entropy production rate, and find that in equilibrium
media with white noises, information swimmers are generally less efficient than
Brownian particles driven by constant forces. For colored noises with long
correlation times, the frequency of measurement can be greatly reduced without
affecting the efficiency of information swimmers.
