We introduce time-ordered multibody interactions to describe complex systems manifesting temporal as well as multibody dependencies. First, we show how the dynamics of multivariate Markov chains can be decomposed in ensembles of time-ordered multibody interactions. Then, we present an algorithm to extract combined interactions from data and a measure to characterize the complexity of interaction ensembles. Finally, we experimentally validate the robustness of our algorithm against statistical errors and its efficiency at obtaining simple interaction ensembles.
翻译:我们引入了有时间顺序的多体互动来描述显示时间和多体依赖的复杂系统。 首先,我们展示了多变量的马尔科夫链的动态如何在时间顺序多体互动的组合中分解。 然后,我们提出了一个从数据中提取混合互动的算法,以及一个描述互动组合复杂性的尺度。 最后,我们实验性地验证了我们算法在统计错误面前的稳健性及其获得简单互动组合的效率。