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In a dissipative system, there exists the (global) attractor which has finitefractal dimensions. The flow on the attractor can be parametrized by a finitenumber of parameters (Temmam 1987). Using machine learning we demonstrate howto construct precise low-dimensional governing equations which are valid insome range of Reynolds number for low-Reynolds-number turbulence in planeCouette flow.

Construction of low-dimensional system reproducing low-Reynolds-number turbulence by machine learning