论文标题
部分可观测时空混沌系统的无模型预测
Hyperaccurate bounds in discrete-state Markovian systems
论文作者
论文摘要
广义经验电流代表了介观系统的大量热力学观察力。它们的波动满足了热力学不确定性关系(TURS),因为它们可以受到平均熵产生的界限。在这里,我们在离散状态马尔可夫系统中的高清电流中得出了一般的闭合表达,即,对于离散时间演变而言,波动最小的电流。我们表明,其相关的高精度结合通常比TURS给出的结合更紧得多,这对于提供平均熵产生的可靠估计可能至关重要。我们还表明,单循环系统(环)仅在有限时表现出高清晰的电流,突出了短期观察的重要性。此外,我们仅作为输入功率或输出功率的函数来得出两个新的界限,以实现工作对工作转换器的效率。最后,我们的理论结果被用来分析均匀梯度的6态模型网络,并在热梯度中表现出耗散驱动的状态选择。
Generalized empirical currents represent a vast class of thermodynamic observables of mesoscopic systems. Their fluctuations satisfy the thermodynamic uncertainty relations (TURs), as they can be bounded by the average entropy production. Here, we derive a general closed expression for the hyperaccurate current in discrete-state Markovian systems, i.e., the one with the least fluctuations, for both discrete- and continuous-time evolution. We show that its associated hyperaccurate bound is generally much tighter than the one given by the TURs, and might be crucial to providing a reliable estimation of the average entropy production. We also show that one-loop systems (rings) exhibit a hyperaccurate current only for finite times, highlighting the importance of short-time observations. Additionally, we derive two novel bounds for the efficiency of work-to-work converters, solely as a function of either the input or the output power. Finally, our theoretical results are employed to analyze a 6-state model network for kinesin, and a chemical system in a thermal gradient exhibiting a dissipation-driven selection of states.