Understanding causation via correlations and linear response theory

Angelo Vulpiani (U Roma 1)

Jun 23. 2021, 14:15 — 14:45

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.

Further Information
ESI Boltzmann Lecture Hall
Associated Event:
Memory Effects in Dynamical Processes: Theory and Computational Implementation (Online Workshop)
Christoph Dellago (U Vienna)
Anja Kuhnhold (U of Freiburg)
Hugues Meyer (U of Saarland)
Tanja Schilling (U of Freiburg)