Patterns Induce Injectivity: A New Thinking in Constructing Injective Local Rules of 1D Cellular Automata over $\mathbb{F}_2$
Defu Lin, Weilin Chen, Chen Wang, Junchi Ma, Chao Wang

TL;DR
This paper introduces a novel approach to constructing reversible 1D cellular automata over _2 by identifying and utilizing stable injective patterns, significantly improving the efficiency of finding such rules.
Contribution
It proposes a new method for designing reversible cellular automata based on injective patterns and offers an efficient algorithm to identify these patterns without exhaustive search.
Findings
Injected patterns remain stable during revolutions.
The proposed algorithms efficiently find injective rules.
New extended patterns enable more reversible CA design.
Abstract
We discovered that certain patterns called injective patterns remain stable during the revolution process, allowing us to create many reversible CA simply by using them to design the revolution rules. By examining injective patterns, we investigated their structural stability during revolutions. This led us to discover extended patterns and pattern mixtures that can create more reversible cellular automata. Furthermore, our research proposed a new way to study the reversibility of CA by observing the structure of local rule . In this paper, we will explicate our study and propose an efficient method for finding the injective patterns. Our algorithms can find injective rules and generate local rule by traversing , instead of to check all injective rules and pick the injective ones.
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Taxonomy
TopicsCellular Automata and Applications · Advanced Data Storage Technologies · DNA and Biological Computing
