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The total lengths of these chains (corresponding to the depth of the evaluation tree) seem to increase roughly like Log[n] for all the rules on this page. … The maximum number of distinct nodes at any level in the tree has large fluctuations but its peaks seem to increase roughly linearly for all the rules on this page (in the Fibonacci case it is Ceiling[n/2] ).
The locality of cellular automaton rules was thought of as making them the analog for symbol sequences of continuous functions for real numbers (compare page 869 ). Of particular interest were invertible (reversible) cellular automaton rules, since systems related by these were considered conjugate or topologically equivalent.
Time reversal invariance would further imply that the rules for going in each direction should be identical. … This means that same rules should apply if one not only reverses the direction of time (T), but also simultaneously inverts all spatial coordinates (P) and conjugates all charges (C), replacing particles by antiparticles.
Huffman coding
From a list p of probabilities for blocks, the list of codewords can be generated using
Map[Drop[Last[#], -1] &, Sort[ Flatten[MapIndexed[Rule, FixedPoint[Replace[Sort[#], {{p0_, i0_}, {p1_, i1_}, pi___} {{p0 + p1, {i0, i1}}, pi}] & , MapIndexed[List, p]] 〚 1, 2 〛 , {-1}]]]] -1
Given the list of codewords c , the sequence of blocks that occur in encoded data d can be uniquely reconstructed using
First[{{}, d} //.
This is achieved for example by the definitions
f[n_] := f[n] = f[n - f[n - 1]] + f[n - f[n - 2]]
f[1] = f[2] = 1
The question of which recursive definitions yield meaningful sequences can depend on the details of how the rules are applied.
[Computing] square roots
A standard way to compute √ n is Newton's method (actually used already in 2000 BC by the Babylonians), in which one takes an estimate of the value x and then successively applies the rule x 1/2 (x + n/x) .
In all cases the rules have been at least slightly more complicated than the ones I consider here, and behavior starting from simple initial conditions does not appear to have been studied before.
The rules for such systems correspond to ordinary differential equations.
The very simplest rules turn out to have difficulties in these regards (see page 1024 ), which is why the model shown in the main text, for example, is on a hexagonal rather than a square grid (compare page 980 ).
Indeed, in most cases, the important features of this behavior will actually turn out to be ones that we have already seen with the various kinds of very simple rules that we have discussed in this chapter .
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