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Thermodynamic cost of computation, algorithmic complexity and the information metric

Nature volume 341, pages 119–124 (1989)Cite this article

Abstract

Algorithmic complexity is a measure of randomness. In contrast to Shannon's entropy it is defined without a recourse to probabilities; for a binary string s it is given by the size, in bits, of the shortest computer program with the output s. I show that algorithmic complexity sets limits on the thermodynamic cost of computations, casts a new light on the limitations of Maxwell's demon and can be used to define distance between binary strings.

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  1. Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, 87545, USA

    W. H. Zurek

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Zurek, W. Thermodynamic cost of computation, algorithmic complexity and the information metric. Nature 341, 119–124 (1989). https://doi.org/10.1038/341119a0

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