Information-theoretic lower bound on energy cost of stochastic computation

Karoline Wiesner, Mile Gu, Elisabeth Rieper, Vlatko Vedral

Research output: Contribution to journalArticle (Academic Journal)peer-review

16 Citations (Scopus)


Physical systems are often simulated using a stochastic computation where different final states result from identical initial states. Here, we derive the minimum energy cost of simulating a data sequence of a general physical system by stochastic computation. We show that the cost is proportional to the difference between two information-theoretic measures of complexity of the data-the statistical complexity and the predictive information. We derive the difference as the amount of information erased during the computation. Finally, we illustrate the physics of information by implementing the stochastic computation as a Gedanken experiment with a Szilard-type engine. The results create a new link between thermodynamics, information theory and complexity.
Original languageEnglish
Pages (from-to)4058-4066
Number of pages9
JournalProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
Issue number2148
Publication statusPublished - 8 Dec 2012


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