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计算速度呈指数级提升:利用DNA实现非确定性通用图灵机

Computing exponentially faster: implementing a non-deterministic universal Turing machine using DNA.

作者信息

Currin Andrew, Korovin Konstantin, Ababi Maria, Roper Katherine, Kell Douglas B, Day Philip J, King Ross D

机构信息

SYNBIOCHEM, Manchester Institute of Biotechnology, University of Manchester, Manchester, UK.

School of Chemistry, University of Manchester, Manchester, UK.

出版信息

J R Soc Interface. 2017 Mar;14(128). doi: 10.1098/rsif.2016.0990.

Abstract

The theory of computer science is based around universal Turing machines (UTMs): abstract machines able to execute all possible algorithms. Modern digital computers are physical embodiments of classical UTMs. For the most important class of problem in computer science, non-deterministic polynomial complete problems, non-deterministic UTMs (NUTMs) are theoretically exponentially faster than both classical UTMs and quantum mechanical UTMs (QUTMs). However, no attempt has previously been made to build an NUTM, and their construction has been regarded as impossible. Here, we demonstrate the first physical design of an NUTM. This design is based on Thue string rewriting systems, and thereby avoids the limitations of most previous DNA computing schemes: all the computation is local (simple edits to strings) so there is no need for communication, and there is no need to order operations. The design exploits DNA's ability to replicate to execute an exponential number of computational paths in P time. Each Thue rewriting step is embodied in a DNA edit implemented using a novel combination of polymerase chain reactions and site-directed mutagenesis. We demonstrate that the design works using both computational modelling and molecular biology experimentation: the design is thermodynamically favourable, microprogramming can be used to encode arbitrary Thue rules, all classes of Thue rule can be implemented, and non-deterministic rule implementation. In an NUTM, the resource limitation is space, which contrasts with classical UTMs and QUTMs where it is time. This fundamental difference enables an NUTM to trade space for time, which is significant for both theoretical computer science and physics. It is also of practical importance, for to quote Richard Feynman 'there's plenty of room at the bottom'. This means that a desktop DNA NUTM could potentially utilize more processors than all the electronic computers in the world combined, and thereby outperform the world's current fastest supercomputer, while consuming a tiny fraction of its energy.

摘要

计算机科学理论基于通用图灵机(UTM):能够执行所有可能算法的抽象机器。现代数字计算机是经典UTM的物理实体。对于计算机科学中最重要的一类问题,即非确定性多项式完全问题,理论上非确定性UTM(NUTM)比经典UTM和量子力学UTM(QUTM)快指数倍。然而,此前从未有人尝试构建NUTM,并且其构建被认为是不可能的。在此,我们展示了NUTM的首个物理设计。该设计基于图厄字符串重写系统,从而避免了大多数先前DNA计算方案的局限性:所有计算都是局部的(对字符串的简单编辑),因此无需通信,也无需对操作进行排序。该设计利用DNA的复制能力在P时间内执行指数数量的计算路径。每个图厄重写步骤都体现在使用聚合酶链反应和定点诱变的新颖组合实现的DNA编辑中。我们通过计算建模和分子生物学实验证明该设计是可行的:该设计在热力学上是有利的,微编程可用于编码任意图厄规则,所有类型的图厄规则都可实现,并且可以实现非确定性规则实现。在NUTM中,资源限制是空间,这与经典UTM和QUTM中资源限制是时间形成对比。这一根本差异使NUTM能够以空间换时间,这对理论计算机科学和物理学都具有重要意义。它也具有实际重要性,正如理查德·费曼所说“底部有很大空间”。这意味着台式DNA NUTM可能潜在地利用比世界上所有电子计算机组合更多的处理器,从而超越世界上当前最快的超级计算机,同时消耗其能量的极小一部分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c30/5378132/67a9d33ae340/rsif20160990-g1.jpg

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