A central problem in uncertainty quantification is how to characterize the impact that our incomplete knowledge about models has on the predictions we make from them. This question naturally lends itself to a probabilistic formulation, by making the unknown model parameters random with given statistics. In the following this approach is used in concert with tools from large deviation theory (LDT) and optimal control to estimate the probability that some observables in a dynamical system go above a large threshold after some time, given the prior statistical information about the system’s parameters and/or its initial conditions. It is established under which conditions the extreme events occur in a predictable way, as the minimizer of the LDT action functional, i.e. the instanton. In the first physical application, the appearance of rogue waves in a long-crested deep sea is investigated. First, the leading order equations are derived for the wave statistics in the framework of wave turbulence (WT), showing that the theory cannot go beyond Gaussianity, although it remains the main tool to understand the energetic transfers. It is shown how by applying our LDT method one can use the incomplete information contained in the spectrum (with the Gaussian statistics of WT) as prior and supplement this information with the governing nonlinear dynamics to reliably estimate the probability distribution of the sea surface elevation far in the tail at later times. Our results indicate that rogue waves occur when the system hits unlikely pockets of wave configurations that trigger large disturbances of the surface height. The rogue wave precursors in these pockets are wave patterns of regular height but with a very specific shape that is identified explicitly, thereby potentially allowing for early detection. Finally, the first experimental evidence of hydrodynamic instantons is presented using data collected in a long wave flume, elevating the instanton description to the role of a unifying theory of extreme water waves. Other applications of the method are illustrated: To the nonlinear Schrödinger equation with random initial conditions, relevant to fiber optics and integrable turbulence, and to a rod with random elasticity pulled by a time-dependent force. The latter represents an interesting nonequilibrium statistical mechanics setup with a strongly out-of-equilibrium transient (absence of local thermodynamic equilibrium) and a small number of degrees of freedom (small system), showing how the LDT method can be exploited to solve optimal-protocol problems.

Large deviations for rare realizations of dynamical systems / Dematteis, Giovanni. - (2019).

Large deviations for rare realizations of dynamical systems

Giovanni Dematteis
2019

Abstract

A central problem in uncertainty quantification is how to characterize the impact that our incomplete knowledge about models has on the predictions we make from them. This question naturally lends itself to a probabilistic formulation, by making the unknown model parameters random with given statistics. In the following this approach is used in concert with tools from large deviation theory (LDT) and optimal control to estimate the probability that some observables in a dynamical system go above a large threshold after some time, given the prior statistical information about the system’s parameters and/or its initial conditions. It is established under which conditions the extreme events occur in a predictable way, as the minimizer of the LDT action functional, i.e. the instanton. In the first physical application, the appearance of rogue waves in a long-crested deep sea is investigated. First, the leading order equations are derived for the wave statistics in the framework of wave turbulence (WT), showing that the theory cannot go beyond Gaussianity, although it remains the main tool to understand the energetic transfers. It is shown how by applying our LDT method one can use the incomplete information contained in the spectrum (with the Gaussian statistics of WT) as prior and supplement this information with the governing nonlinear dynamics to reliably estimate the probability distribution of the sea surface elevation far in the tail at later times. Our results indicate that rogue waves occur when the system hits unlikely pockets of wave configurations that trigger large disturbances of the surface height. The rogue wave precursors in these pockets are wave patterns of regular height but with a very specific shape that is identified explicitly, thereby potentially allowing for early detection. Finally, the first experimental evidence of hydrodynamic instantons is presented using data collected in a long wave flume, elevating the instanton description to the role of a unifying theory of extreme water waves. Other applications of the method are illustrated: To the nonlinear Schrödinger equation with random initial conditions, relevant to fiber optics and integrable turbulence, and to a rod with random elasticity pulled by a time-dependent force. The latter represents an interesting nonequilibrium statistical mechanics setup with a strongly out-of-equilibrium transient (absence of local thermodynamic equilibrium) and a small number of degrees of freedom (small system), showing how the LDT method can be exploited to solve optimal-protocol problems.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2751252
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