EOMC shows that chaotic systems like Lorenz-96 and tokamak turbulence are best captured as metastable switches between persistent low-dimensional manifolds with slowly decreasing exit times.
SIAM journal on scientific computing14(6), 1487–1503 (1993)
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Linearly-scalable and entropy-optimal learning of nonstationary and nonlinear manifolds
EOMC shows that chaotic systems like Lorenz-96 and tokamak turbulence are best captured as metastable switches between persistent low-dimensional manifolds with slowly decreasing exit times.