Primitive recursive functions are defined to deal with non-negative integers and to be set up by combining the basic functions z = 0 & (zero), s = # + 1 & (successor) and p[i_] := Slot[i] & (projection) using the operations of composition and primitive recursion f[0, y___Integer] := g[y] f[x_Integer, y___Integer] := h[f[x - 1, y], x - 1, y] Plus and Times can then for example be defined as plus[0, y_] = y; plus[x_, y_] := s[plus[x - 1, y]] times[0, y_] = 0; times[x_, y_] := plus[times[x - 1, y], y] Most familiar integer mathematical functions also turn out to be primitive recursive—examples being Power , Mod , Binomial , GCD and Prime . … In enumerating recursive functions it is convenient to use symbolic definitions for composition and primitive recursion c[g_, h___] = Apply[g, Through[{h}[##]]] & r[g_, h_] = If[#1  0, g[##2], h[#0[#1 - 1, ##2], #1 - 1, ##2]] & where the more efficient unwound form is r[g_,h_] = Fold[Function[{u, v}, h[u, v, ##2]], g[##2], Range[0, #1 - 1]] & And in terms of these, for example, plus = r[p[1], s] .

Random walks In one dimension, a random walk with t steps of length 1 starting at position 0 can be generated from NestList[(# + (-1)^Random[Integer])&, 0, t] or equivalently FoldList[Plus, 0, Table[(-1)^Random[Integer], {t}]] A generalization to d dimensions is then FoldList[Plus, Table[0, {d}], Table[RotateLeft[PadLeft[ {(-1)^Random[Integer]}, d], Random[Integer, d - 1]], {t}]] A fundamental property of random walks is that after t steps the root mean square displacement from the starting position is proportional to √ t . … To make a random walk on a lattice with k directions in two dimensions, one can set up e = Table[{Cos[2 π s/k], Sin[2 π s/k]}, {s, 0, k - 1}] then use FoldList[Plus, {0, 0}, Table[e 〚 Random[Integer, {1, k}] 〛 , {t}]] It turns out that on any regular lattice, in any number of dimensions, the average behavior of a random walk is always isotropic.

The transitions between these states have probabilities given by m[Map[Length, list]] where m[s_] := With[{q = FoldList[Plus, 0, s]}, ReplacePart[ RotateRight[IdentityMatrix[Last[q]], {0, 1}], 1/Length[s], Flatten[Outer[List, Rest[q], Drop[q, -1] + 1], 1]]] The average spectrum of sequences generated according to these probabilities can be obtained by computing the correlation function for elements a distance r apart ξ [list_, r_] := With[{w = (# - Apply[Plus, #]/Length[#] &)[ Flatten[list]]}, w .

= {}) &];]] ReverseRule[a_  b_, {i_}] := {___, {s[x___, b, y___], {u___}}, ___}  {s[x, a, y], {i, u}} /; FreeQ[s[x], s[a]] In general, there will in principle be more than one such list, and to pick the appropriate list in a practical situation one normally takes the rules of the language to apply with a certain precedence—which is how, for example, x + y z comes to be interpreted in Mathematica as Plus[x, Times[y, z]] rather than Times[Plus[x, y], z] .

Given a sequence of length n , an approximation to h can be reconstructed using Max[MapIndexed[#1/First[#2] &, FoldList[Plus, First[list], Rest[list]]]] The fractional part of the result obtained is always an element of the Farey sequence Union[Flatten[Table[a/b, {b, n}, {a, 0, b}]]] (See also pages 892 , 932 and 1084 .)

In such a rule, given a list of how many neighbors around a given cell (out of s possible) make the cell turn black the outer totalistic code for the rule can be obtained from Apply[Plus, 2^Join[2 list, 2 Range[s + 1] - 1]]

Implementation [of constraint satisfaction] The number of squares violating the constraint used here is given by Cost[list_] := Apply[Plus, Abs[list - RotateLeft[list]]] When applied to all possible patterns, this function yields a distribution with Gaussian tails, but with a sharp point in the middle.

With this setup, each step then corresponds to LifeStep[list_] := With[{p=Flatten[Array[List, {3, 3}, -1], 1]}, With[{u = Split[Sort[Flatten[Outer[Plus, list, p, 1], 1]]]}, Union[Cases[u, {x_, _, _}  x], Intersection[Cases[u, {x_, _, _, _}  x], list]]]] (A still more efficient implementation is based on finding runs of length 3 and 4 in Sort[u] .)

But if IntegerDigits[x, 2] involves no consecutive 0's then for example f[x] can be obtained from 2^(b[Join[{1, 1}, #], Length[#]] &)[IntegerDigits[x, 2]] - 1 a[{l_, _}, r_] := ({l + (5r - 3#)/2, #} &)[Mod[r, 2]] a[{l_, 0}, 0] := {l + 1, 0} a[{l_, 1}, 0] := ({(13 + #(5/2)^IntegerExponent[#, 2])/6, 0} &[6l + 2] b[list_, i_] := First[Fold[a, {Apply[Plus, Drop[list, -i]], 0}, Apply[Plus, Split[Take[list, -i], #1  #2 ≠ 0 &], 1]]] (The corresponding expression for t[x] is more complicated.)

Given p = Array[Prime, Length[list], PrimePi[Max[list]] + 1] or any list of integers that are all relatively prime and above Max[list] (the integers in list are assumed positive) CRT[list_, p_] := With[{m = Apply[Times, p]}, Mod[Apply[Plus, MapThread[#1 (m/#2)^EulerPhi[#2] &, {list, p}]], m]] yields a number x such that Mod[x, p]  list .