{
  "id": "2010.01522",
  "version": "v1",
  "published": "2020-10-04T09:20:46.000Z",
  "updated": "2020-10-04T09:20:46.000Z",
  "title": "Understanding causation via correlations and linear response theory",
  "authors": [
    "Marco Baldovin",
    "Fabio Cecconi",
    "Angelo Vulpiani"
  ],
  "categories": [
    "cond-mat.stat-mech"
  ],
  "abstract": "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.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2020-10-04T09:20:46.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "linear response theory",
      "understanding causation",
      "multi-dimensional linear markov process",
      "generic non-linear dynamics",
      "common-wisdom statement correlation"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}