Chaos & Nonlinear Dynamics — Lorenz Attractor, Bifurcations and Turing Patterns

Tiny differences in initial conditions grow exponentially. Simple equations produce infinite complexity. Stable systems spontaneously break their own symmetry. This is the world of nonlinear dynamics — and our eight interactive simulations let you steer directly into the chaos to understand it.

Strange Attractors

A strange attractor is a set in phase space that a chaotic system approaches but never repeats. It has a fractal dimension — neither a surface (2D) nor a volume (3D), but something in between. The Lorenz attractor has dimension ≈ 2.06; most of phase space is forbidden.

Lorenz System — Standard Parameters

dx/dt = σ(y − x)        [σ ≈ 10 → turbulent Prandtl number]

dy/dt = x(ρ − z) − y    [ρ ≈ 28 → normalised Rayleigh number]

dz/dt = xy − βz        [β ≈ 8/3 → geometric factor]

Lyapunov exponent λ₁ ≈ +0.906 → doubling time ≈ 0.764 s

Attractor dimension D₂ ≈ 2.06 → "thin fractal"

Bifurcations & Period Doubling

A bifurcation is a qualitative change in a dynamical system as a parameter crosses a threshold. The logistic map x_{n+1} = rx_n(1−x_n) exhibits every known route to chaos in a single equation — period-doubling cascades, intermittency, and windows of periodicity deep inside the chaotic regime.

Turing Patterns & Reaction-Diffusion

Alan Turing's 1952 paper "The Chemical Basis of Morphogenesis" predicted that a system of two chemicals — one an activator, one an inhibitor — diffusing at different rates and reacting would spontaneously form spatial patterns from a uniform state. These Turing patterns appear in animal coats, fish skin, and seashell pigmentation.

The Feigenbaum constant δ ≈ 4.6692. In any period-doubling route to chaos — logistic map, Hénon map, driven pendulum, dripping tap — the ratio between successive bifurcation parameter intervals converges to the same universal constant. Mitchell Feigenbaum discovered this in 1975 on a programmable calculator. It was the first demonstration that chaos has universal, quantitative structure.

Algorithms & Methods

RK4 Integration Lyapunov Exponent Estimation Phase-Space Reconstruction Poincaré Section Bifurcation Diagram Sweep Feigenbaum Constant Gray-Scott RD Equations Finite-Difference Laplacian Limit Cycle Detection Period-Doubling Route to Chaos