Approximating the linear response of physical chaos

نویسندگان

چکیده

Abstract Parametric derivatives of statistics are highly desired quantities in prediction, design optimization and uncertainty quantification. In the presence chaos, rigorous computation these is certainly possible, but mathematically complicated computationally expensive. Based on Ruelle’s formalism, this paper shows that sophisticated linear response algorithm can be dramatically simplified higher-dimensional systems featuring statistical homogeneity physical space. We argue contribution SRB (Sinai–Ruelle–Bowen) measure gradient, which an integral yet most cumbersome part full algorithm, negligible if objective function appropriately aligned with unstable manifolds. This abstract condition could potentially satisfied by a vast family real-world chaotic systems, regardless meaning mathematical form perturbed parameter. demonstrate several numerical examples support conclusions present use performance algorithm. experiments, we consider models described differential equations, including Lorenz 96 Kuramoto–Sivashinsky.

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ژورنال

عنوان ژورنال: Nonlinear Dynamics

سال: 2022

ISSN: ['1573-269X', '0924-090X']

DOI: https://doi.org/10.1007/s11071-022-07885-7