Polynomial regression with 512-bit arithmetic reaches machine-precision forecasting of low-dimensional chaotic systems from noise-free data, far exceeding previous valid prediction times.
Theoretical basis and application of an analogue-dynamical model in the Lorenz system
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Machine-Precision Prediction of Low-Dimensional Chaotic Systems from Noise-Free Data
Polynomial regression with 512-bit arithmetic reaches machine-precision forecasting of low-dimensional chaotic systems from noise-free data, far exceeding previous valid prediction times.