论文标题
通过相关和线性响应理论理解因果关系
Understanding causation via correlations and linear response theory
论文作者
论文摘要
尽管（正确的）共同陈述相关性并不意味着因果关系，但适当地使用时间相关性和波动 - 反应理论允许理解多维线性马尔可夫过程的变量之间的因果关系。结果表明，波动反应形式主义既可以用来找到系统变量之间的直接因果关系，并引入一定程度的因果关系，累积时间，其物理解释很简单。尽管对于通用的非线性动力学，相关性和响应函数之间没有简单的确切关系，但所述协议仍然可以在存在弱非线性项的情况下提供有用的代理。
In spite of the (correct) common-wisdom statement correlation does not imply causation, a proper employ of time correlations and of fluctuation-response theory allows to understand the causal relations between the variables of a multi-dimensional linear Markov process. It is shown that the fluctuation-response formalism can be used both to find the direct causal links between the variables of a system and to introduce a degree of causation, cumulative in time, whose physical interpretation is straightforward. Although for generic non-linear dynamics there is no simple exact relationship between correlations and response functions, the described protocol can still give a useful proxy also in presence of weak nonlinear terms.
