Abstract

A new class of deterministic dynamical systems, termed semipredictable dynamical systems, is presented. The spatiotemporal evolution of these systems have both predictable and unpredictable traits, as found in natural complex systems. We prove a general result: The dynamics of any deterministic nonlinear cellular automaton (CA) with pp possible dynamical states can be decomposed at each instant of time in a superposition of NN layers involving p0p_{0}, p1p_{1},... pN−1p_{N-1} dynamical states each, where the pk∈Np_{k\in \mathbb{N}}, k∈[0,N−1]k \in [0, N-1] are divisors of pp. If the divisors coincide with the prime factors of pp this decomposition is unique. Conversely, we also prove that NN CA working on symbols p0p_{0}, p1p_{1},... pN−1p_{N-1} can be composed to create a graded CA rule with NN different layers. We then show that, even when the full spatiotemporal evolution can be unpredictable, certain traits (layers) can exactly be predicted. We present explicit examples of such systems involving compositions of Wolfram's 256 elementary CA and a more complex CA rule acting on a neighborhood of two sites and 12 symbols and whose rule table corresponds to the smallest Moufang loop M12(S3,2)M_{12}(S_{3},2).

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