I’ve posted a new Demonstration, 2D CA Glider Database.
Over at David Eppstein’s page on cellular automata gliders is a database of 21690 different gliders. What do they look like? Here are a few:
The 2D cellular automaton Game of Life determines whether a cell lives, dies or is born by counting the number of live cells in its eight neighboring cells. A living cell is represented by 1 and an empty cell by 0. An empty cell is born to a living cell if it has exactly three living neighbors. A living cell survives if and only if it has two or three neighbors. In shorter form, the Game of Life is B3/S23, encoded as rule 224 in the CellularAutomaton[] function. A cellular automaton rule is applied to an initial condition.
If an initial condition does not change after application of the rule, it is known as a still-life. If the initial condition repeats in the same position after more than one step, it is known as an oscillator. If the initial condition repeats in an offset position, it is known as a glider. One famous initial condition is ((1,1,0),(0,1,1),(1,0,0)) or ,
frequently known as “the Glider”. In addition to the initial condition, a glider has a behavior as it is run by the repeated application of the cellular automaton. Here are four different gliders all starting with
, along with the glider index and a rule giving that behavior.
With the initial condition
, the first row is generated by the Game of Life (B3/S23, rule 224) as well as HighLife (B36/S23, rule 4320), Coagulations (B378/S235678, rule 256224) and Stains (B3678/S235678, rule 260320). In all, the first-row behavior is seen with 256 different rules, with minimum (B3/S23, rule 224) and maximum (B3678/S0235678, rule 260322).
But there are many gliders. 2D CA Glider Database allows you to explore them.
