Lünsmann Benedict J, Kirst Christoph, Timme Marc
Network Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS), 37077 Göttingen, Germany.
Max Planck Institute for the Physics of Complex Systems (MPIPKS), 01187 Dresden, Germany.
PLoS One. 2017 Oct 20;12(10):e0186624. doi: 10.1371/journal.pone.0186624. eCollection 2017.
Across scientific disciplines, thresholded pairwise measures of statistical dependence between time series are taken as proxies for the interactions between the dynamical units of a network. Yet such correlation measures often fail to reflect the underlying physical interactions accurately. Here we systematically study the problem of reconstructing direct physical interaction networks from thresholding correlations. We explicate how local common cause and relay structures, heterogeneous in-degrees and non-local structural properties of the network generally hinder reconstructibility. However, in the limit of weak coupling strengths we prove that stationary systems with dynamics close to a given operating point transition to universal reconstructiblity across all network topologies.
在各科学学科中，时间序列之间的统计依赖性的阈值化成对度量被用作网络动态单元之间相互作用的代理。然而，这种相关性度量往往无法准确反映潜在的物理相互作用。在这里，我们系统地研究了从阈值化相关性重建直接物理相互作用网络的问题。我们阐明了局部共同原因和中继结构、网络入度的异质性以及非局部结构特性通常如何阻碍可重建性。然而，在弱耦合强度的极限情况下，我们证明，动力学接近给定工作点的平稳系统在所有网络拓扑中都转变为通用可重建性。
