Algorithmic Complexity in Noise Induced Transport Systems

Abstract

Time correlated fluctuations interacting with a spatial asymmetry potential are sufficient conditions to give rise to transport of Brownian particles. The transfer of information coming from the nonequilibrium bath, viewed as a source of negentropy, give rise to the correlated noise. The algorithmic complexity of an object provides a means of quantitating its information contents. The Kolmogorov information entropy or algorithmic complexity is investigated in order to quantitate the transfer of information that occurs in computational models showing noise induced transport. The complexity is measured in terms of the average number of bits per time unit necessary to specify the sequence generated by the system.