2017/06/30 by Dominique Chu · 3 citations
Computer Science · Mathematics · Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics #Algorithm #Applied mathematics #Computation #Computer science #Energy (signal processing) #Energy consumption #Geometry #Markov process #Mathematics #Physics #Quantum Computing Algorithms and Architecture #Quantum many-body systems #Scaling #Statistical physics #Statistics #cond-mat.stat-mech
paper · pdf · open access · doi:10.1103/physreve.97.022121
published in Physical review. E 97(2), 022121 (American Physical Society) · 15 pages, 4 figures
arxiv created 2018/02/06 · openalex publication_date 2018/02/15 · arxiv updated 2018/02/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
A central result of stochastic thermodynamics is that irreversible state transitions of Markovian systems entail a cost in terms of an infinite entropy production. A corollary of this is that strictly deterministic computation is not possible. Using a thermodynamically consistent model, we show that quasideterministic computation can be achieved at finite, and indeed modest cost with accuracies that are indistinguishable from deterministic behavior for all practical purposes. Concretely, we consider the entropy production of stochastic (Markovian) systems that behave like and and a not gates. Combinations of these gates can implement any logical function. We require that these gates return the correct result with a probability that is very close to 1, and additionally, that they do so within finite time. The central component of the model is a machine that can read and write binary tapes. We find that the error probability of the computation of these gates falls with the power of the system size, whereas the cost only increases linearly with the system size.