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Semipredictable dynamical systems
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DOI：10.1016/j.cnsns.2016.02.022.png)
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Abstract
En 中文
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 p possible dynamical states can be decomposed at each instant of time in a superposition of N layers involving p(0), p(1), ..., p(N-1) dynamical states each, where the p(k is an element of N), k is an element of [0, N - 1] are divisors of p. If the divisors coincide with the prime factors of p this decomposition is unique. Conversely, we also prove that N CA working on symbols p(0), p(1), ... , p(N-1) can be composed to create a graded CA rule with N 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 M-12(S-3, 2). (C) 2016 Elsevier B.V. All rights reserved.
Keywords:
Complexity
Predictability
Time series
Cellular automata
Moufang loops
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