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We show that the evolution of any dynamical system is related to a predictive asymmetry that quantifies causal connections from limited observations.

We present two new methods for generating uni- and multivariate surrogate data derived from transfer operator approximation. We demonstrate how these surrogates can be used to produce more reliable statistics for the underlying dynamics, such as attractor dimension estimates.