Zanin Massimiliano
Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), Campus UIB, 07122 Palma de Mallorca, Spain.
Chaos. 2021 Oct;31(10):103118. doi: 10.1063/5.0067342.
Time irreversibility, defined as the lack of invariance of the statistical properties of a system or time series under the operation of time reversal, has received increasing attention during the last few decades, thanks to the information it provides about the mechanisms underlying the observed dynamics. Following the need of analyzing real-world time series, many irreversibility metrics and tests have been proposed, each one associated with different requirements in terms of, e.g., minimum time series length or computational cost. We here build upon previously proposed tests based on the concept of permutation patterns but deviating from them through the inclusion of information about the amplitude of the signal and how this evolves over time. We show, by means of synthetic time series, that the results yielded by this method are complementary to the ones obtained by using permutation patterns alone, thus suggesting that "one irreversibility metric does not fit all." We further apply the proposed metric to the analysis of two real-world data sets.
时间不可逆性被定义为在时间反演操作下系统或时间序列的统计特性缺乏不变性，在过去几十年中受到了越来越多的关注，这得益于它所提供的关于观测到的动力学背后机制的信息。随着分析现实世界时间序列的需求，人们提出了许多不可逆性度量和检验方法，每种方法在例如最小时间序列长度或计算成本等方面都有不同的要求。我们在此基础上，基于排列模式的概念构建了先前提出的检验方法，但通过纳入有关信号幅度及其随时间演变的信息而与它们有所不同。我们通过合成时间序列表明，该方法产生的结果与仅使用排列模式获得的结果互补，从而表明“一种不可逆性度量并不适用于所有情况”。我们进一步将所提出的度量应用于两个现实世界数据集的分析。
