Thermodynamics of Statistical Inference by Cells
Thermodynamics of Statistical Inference by Cells
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DOI：
10.1103/physrevlett.113.148103
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发表时间：
2014-10-03
影响因子：
8.6
通讯作者：
Mehta, Pankaj
中科院分区：
文献类型：
--
作者：
Lang, Alex H.;Fisher, Charles K.;Mehta, Pankaj
热力学、计算和信息之间的深层联系现在在理论和实验上都得到了很好的建立。在这里，我们扩展这些想法，表明热力学也对统计估计和学习的基本约束。要做到这一点，我们调查（非平衡态）热力学生化信号网络的能力，以估计外部信号的浓度的限制。我们表明，准确性是有限的能源消耗，这表明统计推断有基本的热力学约束。
The deep connection between thermodynamics, computation, and information is now well established both theoretically and experimentally. Here, we extend these ideas to show that thermodynamics also places fundamental constraints on statistical estimation and learning. To do so, we investigate the constraints placed by (nonequilibrium) thermodynamics on the ability of biochemical signaling networks to estimate the concentration of an external signal. We show that accuracy is limited by energy consumption, suggesting that there are fundamental thermodynamic constraints on statistical inference.