
Nonlinearity in Large-Cycle Cellular Automata
Sukanya Mukherjee
Department of Computer Science and Engineering
Institute of Engineering and Management Kolkata
University of Engineering and Management, Kolkata
700091, West Bengal, India
sukanyaiem@gmail.com
Sumit Adak
Department of Applied Mathematics and Computer Science
DTU Compute, Technical University of Denmark
Kgs. Lyngby, Denmark, 2800
suad@dtu.dk
Abstract
The class of maximal-length cellular automata (CAs) has gained significant attention over the last few years due to the fact that it can generate cycles with the longest possible lengths. For every l of the form where n∈N, a cycle of length l can be generated by a cellular automaton (CA) of size ; this maximal-length CA is in fact the optimal (minimum-sized) CA to generate a cycle of length l. However, maximal-length CAs are, in general, linear and have some drawbacks. Moreover, it is nontrivial to address this problem for any l∈N, that is, removing the constraint that l is of the form . In this paper we therefore employ nonlinearity in the rules and aim to generate the near-optimal CA for any given cycle length l, meaning that the generated CAs will be of size , where the displacement d is as small as possible. We use a generic operator to concatenate a collection of component CAs of sizes by employing an evolutionary strategy. Here, and , where (1≤i≤k) is the maximum cycle length of a CA of size . An influencing factor in the design of component CAs is to achieve the near-optimal CA for a given cycle length. Here we consider nonlinear reversible large-cycle CAs as component CAs. We also measure the effectiveness of nonlinearity in large-cycle generation.
Keywords: cellular automata; CAs; reversible CAs; large-cycle CA; nonlinearity; neighborhood dependent; evolution
Cite this publication as:
S. Mukherjee and S. Adak, “Nonlinearity in Large-Cycle Cellular Automata,” Complex Systems, 34(1), 2025 pp. 129–160.
https://doi.org/10.25088/ComplexSystems.34.1.129