The drawings

Every drawing on this site comes from one of twelve systems in three families: chaotic flows, self-similar figures and neural networks. A seed picks the system and every random choice in it, so the same seed always gives the same drawing. Here is each one, drawn from a single seed. A thirteenth, a spiral that escapes, lives on the page you get at a broken link.

Chaotic

  • Lorenz system

    dx/dt = σ(y − x)dy/dt = x(ρ − z) − ydz/dt = xy − βzσ = 10, ρ = 28, β = 8/3

    Edward Lorenz’s 1963 model of convection in the atmosphere. Start it a hair differently and it soon takes a completely different path: the butterfly effect.

    Seed 100043 · Draw this on the home page

  • Rössler system

    dx/dt = −y − zdy/dt = x + aydz/dt = b + z(x − c)a = 0.2, b = 0.2, c = 5.7

    Otto Rössler’s 1976 system, designed to behave like Lorenz’s but be easier to analyse: a spiral band that keeps folding back into itself.

    Seed 100026 · Draw this on the home page

  • Aizawa attractor

    dx/dt = (z − b)x − dydy/dt = dx + (z − b)ydz/dt = c + az − z³/3 − (x² + y²)(1 + ez) + fzx³a = 0.95, b = 0.7, c = 0.6, d = 3.5, e = 0.25, f = 0.1

    A three-variable chaotic flow whose single trajectory traces a sphere-like shape with a tube running along its axis.

    Seed 100010 · Draw this on the home page

  • Halvorsen attractor

    dx/dt = −ax − 4y − 4z − y²dy/dt = −ay − 4z − 4x − z²dz/dt = −az − 4x − 4y − x²a = 1.4

    A chaotic flow with cyclic symmetry: shift its three variables round (x to y, y to z, z to x) and the equations stay the same.

    Seed 100003 · Draw this on the home page

  • Forced Duffing oscillator

    dx/dt = vdv/dt = −δv + x − x³ + γ cos ωtδ = 0.3, γ = 0.5, ω = 1.2

    A periodically pushed spring with two resting points, a form of the equation Georg Duffing studied in 1918. With the right push, its motion never settles.

    Seed 100012 · Draw this on the home page

Self-similar

  • Heighway dragon

    start: FF → F+GG → F−GF and G draw a step, + and − turn 90°rewritten 10 to 12 times

    Fold a strip of paper in half again and again, then open every fold to a right angle: this is the shape. Found by NASA physicists John Heighway, Bruce Banks and William Harter in the 1960s.

    Seed 100025 · Draw this on the home page

  • Sierpiński arrowhead

    start: AA → B−A−BB → A+B+AA and B draw a step, + and − turn 60°rewritten 6 or 7 times

    One unbroken line that traces out Wacław Sierpiński’s triangle.

    Seed 100053 · Draw this on the home page

  • Gosper curve

    start: AA → A−B−−B+A++AA+B−B → +A−BB−−B−A++A+BA and B draw a step, + and − turn 60°rewritten 4 or 5 times

    Bill Gosper’s “flowsnake”: a single line that fills hexagon-like islands, each made of smaller copies of itself.

    Seed 100013 · Draw this on the home page

  • Barnsley fern

    each point (x, y) becomes, at random: 1% (0, 0.16y)85% (0.85x + 0.04y, −0.04x + 0.85y + 1.6) 7% (0.2x − 0.26y, 0.23x + 0.22y + 1.6) 7% (−0.15x + 0.28y, 0.26x + 0.24y + 0.44)

    Michael Barnsley’s fern, made by applying four simple maps at random, one point at a time.

    Seed 100006 · Draw this on the home page

Neural

  • Growing neuron

    branch → grow, wander, fork, thin

    A neuron grown from a few rules: branches extend, wander slightly, fork and thin out, and the short ticks are spines. Santiago Ramón y Cajal drew neurons like this in India ink, from tissue stained with Camillo Golgi’s method. Each seed grows a pyramidal neuron, a stellate neuron or a Purkinje cell.

    Seed 100013 · Draw this on the home page

  • Chaotic network

    dx/dt = −x + J·tanh(x), J ~ N(0, g²/N), N = 100, g = 2.2

    A hundred model neurons, each connected to every other at random. Sompolinsky, Crisanti and Sommers showed in 1988 that once the connections are strong enough, the activity of such networks becomes chaotic. Drawn here: that activity, projected onto its three main directions of variation.

    Seed 100012 · Draw this on the home page

  • 01234567898 · 0.997 · 0.999 · 0.993 · 0.54it was a 2

    Digit reader

    64 → 16 → 10, tanh, softmax, Adam

    A small network reading handwritten digits it never saw in training. The pen draws each digit, the hidden units it activates and the five that push hardest for the answer, then writes the answer and the network’s score for it; earlier answers fade. The digits come from a dataset Alpaydin and Kaynak published in 1998: handwriting collected on preprinted forms and reduced to 8×8 grids by counting the inked pixels in each block (UCI Machine Learning Repository, CC BY 4.0). On 450 held-out digits it gets 97% right, and the drawing shows its mistakes too.

    Seed 100007 · Draw this on the home page