Rössler, Hénon, Clifford - beautiful patterns from simple equations
A strange attractor is the geometric shape that a chaotic system traces out over time. Despite being unpredictable moment-to-moment, the system is drawn irresistibly to this fractal structure - never repeating, but never escaping.
Each attractor shown here arises from just 3 simple equations. From these minimal rules emerge infinitely complex, beautiful structures - the fingerprints of chaos itself.
These attractors arise from systems of three coupled differential equations. A particle following these equations traces out endlessly complex paths:
The butterfly that started chaos theory (1963)
Drag to rotate, scroll to zoom. Each attractor is a chaotic system that never repeats but stays bounded within a fractal shape.
Strange attractors have non-integer dimensions. The Lorenz attractor has dimension ~2.06 - more than a surface but less than a solid.
Nearby trajectories diverge exponentially. This is the butterfly effect - tiny differences lead to completely different paths.
Every trajectory comes arbitrarily close to every point on the attractor. The whole structure is the orbit's closure.
These attractors come from discrete maps rather than differential equations. Each point maps to a new position, creating intricate density patterns over millions of iterations:
Elegant curves with sine/cosine (Peter de Jong)
These iterated function systems create intricate patterns by applying simple transformations millions of times. Adjust the parameters to explore an infinite variety of forms.
The butterfly that started chaos theory. Edward Lorenz discovered it while modeling weather convection. Its two wings represent two weather modes.
Otto Rössler designed this as the simplest possible 3D chaotic system. It has a single spiral that occasionally jumps to a higher loop.
These 2D attractors use sine and cosine functions to create flowing, organic patterns. Every choice of parameters yields a unique artwork.
Atmospheric dynamics exhibit strange attractors, explaining why long-term weather prediction is fundamentally limited.
The healthy heart shows chaotic variability. Too much regularity can actually indicate heart disease.
Financial markets display chaotic behavior, with small events potentially triggering large market movements.
Brain dynamics may operate at the edge of chaos, balancing stability with the flexibility needed for thought.