CCSS summer schoolCellular Automata simulator

steps 0
grid average ⟨s⟩ 0.000
speed 10 /s

Implemented Dynamics

Vegetation Turing Pattern: Short-range facilitation (radius R1 with weight w1) promotes growth while longer-range inhibition (radius R2 with weight w2) restricts it.

Simplified Ising CA: Spins flip toward local alignment, modulated by global bias H and noise probability P.

Schelling Segregation: Agents evaluate neighborhood similarity within radius R=1. Unhappy cells flip state to simulate relocation.

Conway's Game of Life: Classic 2D cellular automaton governed by local birth/survival rules (B3/S23). Includes initial preset structures and full dynamic **RLE parser** compatibility.

Mean-Field Population (Global ρ): Each cell only knows its own state and the global density ρ (fraction of cells ON). Independent per-cell flips: OFF→ON w.p. ε+αρ², ON→OFF w.p. δ. No macro rule is imposed — averaging these independent micro-flips over the population is what produces the cubic ṡ = (1−s)(ε+αs²) − δs, whose saddle-node bifurcations (in δ) give hysteresis. Use the Sweep Up/Down buttons to ramp δ automatically, holding each value long enough to equilibrate, and watch the loop trace out on the right-hand chart.

Mean-Field Population (Local ρ): Identical micro-rule to the global version, but each cell uses its own local neighborhood average ρᵢ (set by the radius slider) instead of the global average. Comparing the two shows how a finite interaction range shifts the effective tipping points and introduces spatial nucleation noise relative to the true mean-field limit.

Custom Code Rule: Live dynamic JavaScript evaluation per cell for customized CA experimentation.