title: Data-driven prediction and prevention of extreme events in a spatially extended excitable system.
abstract: Extreme events occur in many spatially extended dynamical systems, often devastatingly affecting human life, which makes their reliable prediction and efficient prevention highly desirable. We study the prediction and prevention of extreme events in a spatially extended system, a system of coupled FitzHugh-Nagumo units, in which extreme events occur in a spatially and temporally irregular way. Mimicking typical constraints faced in field studies, we assume not to know the governing equations of motion and to be able to observe only a subset of all phase-space variables for a limited period of time. Based on reconstructing the local dynamics from data and despite being challenged by the rareness of events, we are able to predict extreme events remarkably well. With small, rare, and spatiotemporally localized perturbations which are guided by our predictions, we are able to completely suppress extreme events in this system.
authors.affiliation: Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Straße 38, 01187 Dresden, Germany.
authors.forename: Stephan
authors.initials: S
authors.lastname: Bialonski
authors.affiliation: Department of Epileptology, University of Bonn, Sigmund-Freud-Straße 25, 53105 Bonn, Germany.|Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14-16, 53115 Bonn, Germany.|Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53175 Bonn, Germany.
authors.forename: Gerrit
authors.initials: G
authors.lastname: Ansmann
authors.affiliation: Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Straße 38, 01187 Dresden, Germany.
authors.forename: Holger
authors.initials: H
authors.lastname: Kantz
mesh_terms: D017711:Nonlinear Dynamics; D062211:Spatio-Temporal Analysis; D013223:Statistics as Topic