Laboratoire de Physico-Chimie Théorique - UMR CNRS Gulliver 7083, ESPCI, 10 rue Vauquelin, F-75231 Paris, France.
J Chem Phys. 2013 Sep 28;139(12):124109. doi: 10.1063/1.4821760.
We show how to extract an estimate of the entropy production from a sufficiently long time series of stationary fluctuations of chemical reactions. This method, which is based on recent work on fluctuation theorems, is direct, non-invasive, does not require any knowledge about the underlying dynamics and is applicable even when only partial information is available. We apply it to simple stochastic models of chemical reactions involving a finite number of states, and for this case, we study how the estimate of dissipation is affected by the degree of coarse-graining present in the input data.
我们展示了如何从足够长的化学反静态波动时间序列中提取熵产生的估计值。该方法基于最近关于涨落定理的研究,直接、非侵入式,不需要关于潜在动力学的任何知识,即使只有部分信息可用,也可适用。我们将其应用于涉及有限状态的简单随机化学反应模型,并针对这种情况,研究了在输入数据中存在的粗粒化程度如何影响耗散的估计值。