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arXiv 2010.01152cond-mat.stat-mechcs.ETmath.DSphysics.comp-ph
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非马尔可夫动量计算:通用和高效

Non-Markovian Momentum Computing: Universal and Efficient

Kyle J. Ray, Gregory W. Wimsatt, Alexander B. Boyd, James P. Crutchfield

摘要:

所有的计算都是物理嵌入的。考虑到这一点,越来越多的结果将速率方程作为热力学计算和生物信息处理的基础机制。然而,严格应用隐含的连续时间马尔可夫链,排除了自然计算的范围。我们表明,扩展工具集的连续时间隐马尔可夫链基本上消除了限制。一般的观点是具体的,我们分析了两个非常有用的计算,是不可能描述的一组速率方程的记忆状态。我们设计和分析了一个无成本的位翻转,提供了第一个反例速率方程建模。我们将其推广到一个无代价的Fredkin门-可逆计算中的一个关键操作,它是计算通用的。超越速率方程动力学不仅是可能的,而且是必要的,如果随机热力学要成为物理信息处理范式的一部分。

英文摘要:

All computation is physically embedded. Reflecting this, a growing body of results embraces rate equations as the underlying mechanics of thermodynamic computation and biological information processing. Strictly applying the implied continuous-time Markov chains, however, excludes a universe of natural computing. We show that expanding the toolset to continuous-time hidden Markov chains substantially removes the constraints. The general point is made concrete by our analyzing two eminently-useful computations that are impossible to describe with a set of rate equations over the memory states. We design and analyze a thermodynamically-costless bit flip, providing a first counterexample to rate-equation modeling. We generalize this to a costless Fredkin gate---a key operation in reversible computing that is computation universal. Going beyond rate-equation dynamics is not only possible, but necessary if stochastic thermodynamics is to become part of the paradigm for physical information processing.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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