Role of sufficient statistics in stochastic thermodynamics and its implication to sensory adaptation
Role of sufficient statistics in stochastic thermodynamics and its implication to sensory adaptation
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充分统计在随机热力学中的作用及其对感觉适应的影响
DOI：
10.1103/physreve.97.042103
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Takumi Matsumoto and Takahiro Sagawa
中科院分区：
文献类型：
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作者：
Takumi Matsumoto and Takahiro Sagawa
充分统计量是统计学中的一个重要概念，它意味着具有推理任务所需的足够信息的概率变量。我们研究充分统计量和相关量在随机热力学中的作用。具体来说，我们证明了一般的连续时间二分网络，存在一个充分的统计意味着一个信息量称为感觉能力采取最大值。由于最大的感觉能力施加了一个约束，能量效率不能超过一半，我们的结果意味着，存在一个足够的统计是不可避免地伴随着能量耗散。我们还表明，在一个特定的参数区域的线性Langevin系统存在的最佳噪声强度，在该最佳噪声强度的感觉能力，信息热力学效率，和总熵产生同时优化。我们应用我们的一般结果的感觉适应模型的E。Coliand发现感觉能力在实验现实参数下几乎是最大的。
A sufficient statistic is a significant concept in statistics, which means a probability variable that has sufficient information required for an inference task. We investigate the roles of sufficient statistics and related quantities in stochastic thermodynamics. Specifically, we prove that for general continuous-time bipartite networks, the existence of a sufficient statistic implies that an informational quantity called the sensory capacity takes the maximum. Since the maximal sensory capacity imposes a constraint that the energetic efficiency cannot exceed one-half, our result implies that the existence of a sufficient statistic is inevitably accompanied by energetic dissipation. We also show that, in a particular parameter region of linear Langevin systems there exists the optimal noise intensity at which the sensory capacity, the information-thermodynamic efficiency, and the total entropy production are optimized at the same time. We apply our general result to a model of sensory adaptation ofE. coliand find that the sensory capacity is nearly maximal with experimentally realistic parameters.