cellular_automaton


cellular_automaton, a Python code which prints or plots the evolution of Cellular Automaton rule #30.

Given an initial linear array of 0's and 1's, rule 30 produces a new array using transformations based on each value and the value of its left and right neighbors, as follows:

      111  110  101  100  011  010  001  000
       V    V    V    V    V    V    V    V
       0    0    0    1    1    1    1    0     
      
Note that there are 256 = 2^8 possible ways to fill in this output chart, and that rule 30 gets its index by the fact that (0,0,0,1,1,1,1,0) can be interpreted as the binary representation of 30.

For instance, if the current values of X(4), X(5) and X(6) are 0, 1 and 1, respectively, then the new value of X(5) will be 1.

The first and last entries of the array must be treated specially, since they don't have a left or right neighbor. One simple treatment is to assume that there are phantom neighbors whose values are both 0. Another is to enforce periodic boundary conditions.

Licensing:

The computer code and data files described and made available on this web page are distributed under the MIT license

Languages:

cellular_automaton is available in a C version and a C++ version and a Fortran90 version and a MATLAB version and an Octave version and a Python version.

Related Data and Programs:

brownian_motion_simulation, a Python code which simulates Brownian motion in an M-dimensional region.

random_walk_2d_simulation, a Python code which simulates a random walk in a 2-dimensional region.

sir_simulation, a Python code which simulates the spread of a disease through a hospital room of M by N beds, using the Susceptible/Infected/Recovered (SIR) model.

Reference:

  1. Stephen Wolfram,
    A New Kind of Science,
    Wolfram Media, 2002,
    ISBN13: 978-1579550080,
    LC: QA267.5.C45.W67.

Source Code:


Last revised on 06 December 2022.