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Observation-based correction of dynamical models using thermostats
Author(s) -
Keith W. Myerscough,
Jason Frank,
Benedict Leimkuhler
Publication year - 2017
Publication title -
proceedings of the royal society a mathematical physical and engineering sciences
Language(s) - English
Resource type - Journals
eISSN - 1471-2946
pISSN - 1364-5021
DOI - 10.1098/rspa.2016.0730
Subject(s) - thermostat , convergence (economics) , term (time) , statistical physics , dynamical systems theory , transient (computer programming) , work (physics) , dynamical system (definition) , trajectory , set (abstract data type) , control theory (sociology) , state (computer science) , point (geometry) , computer science , mathematics , physics , algorithm , control (management) , thermodynamics , artificial intelligence , geometry , quantum mechanics , astronomy , economics , programming language , economic growth , operating system
Models used in simulation may give accurate short-term trajectories but distort long-term (statistical) properties. In this work, we augment a given approximate model with a control law (a ‘thermostat’) that gently perturbs the dynamical system to target a thermodynamic state consistent with a set of prescribed (possibly evolving) observations. As proof of concept, we provide an example involving a point vortex fluid model on the sphere, for which we show convergence of equilibrium quantities (in the stationary case) and the ability of the thermostat to dynamically track a transient state.

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