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We study an information-based mechanism of self-propulsion in noisyenvironment. An information swimmer maintains directional motion byperiodically measuring its velocity and accordingly adjusting its frictioncoefficient. Assuming that the measurement and adjustment are reversible andhence cause no energy dissipation, an information swimmer may move withoutexternal energy input. There is however no violation of the second law ofthermodynamics, because the information entropy stored in the memory of swimmerincreases monotonically. By optimizing its control parameters, the swimmer canachieve a steady velocity that is comparable to the root-mean-square velocityof an analogous Brownian particle. We also define a swimming efficiency interms of information entropy production rate, and find that in equilibriummedia with white noises, information swimmers are generally less efficient thanBrownian particles driven by constant forces. For colored noises with longcorrelation times, the frequency of measurement can be greatly reduced withoutaffecting the efficiency of information swimmers.

Information Swimmer: A Novel Mechanism of Self-propulsion