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Register a new userA New Parameter $F$ to Classify Cellular Automata Rule Table Space and a Phase Diagram in $lambda-F$ Plane
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It is shown that for the N-neighbor and K-state cellular automata, the class II, class III and class IV patterns coexist at least in the range $frac{1}{K} le lambda le 1-frac{1}{K} $. The mechanism which determines the difference between the pattern classes at a fixed $lambda$ is found, and it is studied quantitatively by introducing a new parameter $F$. Using the parameter F and $lambda$, the phase diagram of cellular automata is obtained for 5-neighbor and 4-state cellular automata. PACS: 89.75.-k Complex Systems
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In addition to the $lambda$ parameter, we have found another parameter which characterize the class III, class II and class IV patterns more quantitatively. It explains why the different classes of patterns coexist at the same $lambda$. With this parameter, the phase diagram for an one dimensional cellular automata is obtained. Our result explains why the edge of chaos(class IV) is scattered rather wide range in $lambda$ around 0.5, and presents an effective way to control the pattern classes. oindent PACS: 89.75.-k Complex Systems
The mechanism which discriminates the pattern classes at the same $lambda$, is found. It is closely related to the structure of the rule table and expressed by the numbers of the rules which break the strings of the quiescent states. It is shown that for the N-neighbor and K-state cellular automata, the class I, class II, class III and class IV patterns coexist at least in the range, $frac{1}{K} le lambda le 1-frac{1}{K} $. The mechanism is studied quantitatively by introducing a new parameter $F$, which we call quiescent string dominance parameter. It is taken to be orthogonal to $lambda$. Using the parameter F and $lambda$, the rule tables of one dimensional 5-neighbor and 4-state cellular automata are classified. The distribution of the four pattern classes in ($lambda$,F) plane shows that the rule tables of class III pattern class are distributed in larger $F$ region, while those of class II and class I pattern classes are found in the smaller $F$ region and the class IV behaviors are observed in the overlap region between them. These distributions are almost independent of $lambda$ at least in the range $0.25 leq lambda leq 0.75$, namely the overlapping region in $F$, where the class III and class II patterns coexist, has quite gentle $lambda$ dependence in this $lambda$ region. Therefore the relation between the pattern classes and the $lambda$ parameter is not observed. PACS: 89.75.-k Complex Systems
This paper proposes several algorithms and their Cellular Automata Machine (CAM) for drawing the State Transition Diagram (STD) of an arbitrary Cellular Automata (CA) Rule (any neighborhood, uniform/ hybrid and null/ periodic boundary) and length of the CA n. It also discusses the novelty, hardware cost and the complexities of these algorithms.
We define a new transfinite time model of computation, infinite time cellular automata. The model is shown to be as powerful than infinite time Turing machines, both on finite and infinite inputs; thus inheriting many of its properties. We then show how to simulate the canonical real computation model, BSS machines, with infinite time cellular automata in exactly omega steps.
In this paper, linear Cellular Automta (CA) rules are recursively generated using a binary tree rooted at 0. Some mathematical results on linear as well as non-linear CA rules are derived. Integers associated with linear CA rules are defined as linear numbers and the properties of these linear numbers are studied.
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