Smith Eric
Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA.
J Theor Biol. 2008 May 21;252(2):213-20. doi: 10.1016/j.jtbi.2008.02.013. Epub 2008 Feb 16.
This is the third in a series of three papers devoted to energy flow and entropy changes in chemical and biological processes, and their relations to the thermodynamics of computation. The previous two papers have developed reversible chemical transformations as idealizations for studying physiology and natural selection, and derived bounds from the second law of thermodynamics, between information gain in an ensemble and the chemical work required to produce it. This paper concerns the explicit mapping of chemistry to computation, and particularly the Landauer decomposition of irreversible computations, in which reversible logical operations generating no heat are separated from heat-generating erasure steps which are logically irreversible but thermodynamically reversible. The Landauer arrangement of computation is shown to produce the same entropy-flow diagram as that of the chemical Carnot cycles used in the second paper of the series to idealize physiological cycles. The specific application of computation to data compression and error-correcting encoding also makes possible a Landauer analysis of the somewhat different problem of optimal molecular recognition, which has been considered as an information theory problem. It is shown here that bounds on maximum sequence discrimination from the enthalpy of complex formation, although derived from the same logical model as the Shannon theorem for channel capacity, arise from exactly the opposite model for erasure.
这是关于化学和生物过程中的能量流动与熵变及其与计算热力学关系的三篇系列论文中的第三篇。前两篇论文将可逆化学转化作为研究生理学和自然选择的理想化模型,并从热力学第二定律推导出了集合中信息增益与产生该信息所需化学功之间的界限。本文关注化学与计算的显式映射,特别是不可逆计算的兰道尔分解,其中不产生热量的可逆逻辑操作与逻辑上不可逆但热力学上可逆的产生热量的擦除步骤相分离。结果表明,计算的兰道尔布局产生的熵流图与该系列第二篇论文中用于理想化生理循环的化学卡诺循环的熵流图相同。计算在数据压缩和纠错编码方面的具体应用,也使得对最优分子识别这一略有不同问题进行兰道尔分析成为可能,最优分子识别一直被视为一个信息论问题。本文表明,从复合物形成焓得出的最大序列区分界限,尽管与信道容量的香农定理基于相同的逻辑模型,但却是由完全相反的擦除模型得出的。