有限分辨率下的耗散:幂律和隐藏耗散尺度的检测

Qiwei Yu, Pedro E. Harunari
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引用次数: 0

摘要

非平衡系统,特别是生物体,是通过能量的不可逆转化来维持的,而能量的不可逆转化驱动着各种功能。然而,现有的技术通常忽略了实验的局限性,要么假定信息充分,要么采用需要了解隐藏自由度背后结构的粗粒度方法。在这里,我们研究了从有限分辨率测量中推断耗散的方法,采用了最近开发的无模型估计器,该估计器同时考虑了粗粒度转换序列和等待时间分布:$\sigma_2=\sigma_2^\ell + \sigma_2^t$。主要项$\sigma_2^\ell$源自观测到的转换序列;我们发现它与分辨率呈幂律关系。将缩放指数与以前的估计值进行比较,突出了在较低分辨率下考虑通量相关性的重要性。$sigma_2^t$ 来自等待时间分布的不对称性,其峰值揭示了底层耗散过程的特征尺度。或者,特征尺度可以从 $\sigma_2^\ell$ 的比例交叉中检测到。这为直接从耗散测量中提取隐藏的特征耗散尺度提供了一个新的视角。我们用生化模型和复杂网络来说明这些结果。总之,这项研究强调了在非平衡系统中考虑分辨率的重要性,提供了对实验分辨率、熵产生和潜在复杂性之间相互作用的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dissipation at limited resolutions: Power law and detection of hidden dissipative scales
Nonequilibrium systems, in particular living organisms, are maintained by irreversible transformations of energy that drive diverse functions. Quantifying their irreversibility, as measured by energy dissipation, is essential for understanding the underlying mechanisms. However, existing techniques usually overlook experimental limitations, either by assuming full information or by employing a coarse-graining method that requires knowledge of the structure behind hidden degrees of freedom. Here, we study the inference of dissipation from finite-resolution measurements by employing a recently developed model-free estimator that considers both the sequence of coarse-grained transitions and the waiting time distributions: $\sigma_2=\sigma_2^\ell + \sigma_2^t$. The dominant term $\sigma_2^\ell$ originates from the sequence of observed transitions; we find that it scales with resolution following a power law. Comparing the scaling exponent with a previous estimator highlights the importance of accounting for flux correlations at lower resolutions. $\sigma_2^t$ comes from asymmetries in waiting time distributions, with its peak revealing characteristic scales of the underlying dissipative process. Alternatively, the characteristic scale can be detected in a crossover of the scaling of $\sigma_2^\ell$. This provides a novel perspective for extracting otherwise hidden characteristic dissipative scales directly from dissipation measurements. We illustrate these results in biochemical models as well as complex networks. Overall, this study highlights the significance of resolution considerations in nonequilibrium systems, providing insights into the interplay between experimental resolution, entropy production, and underlying complexity.
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