Diffusion-Limited Aggregation

Watch random-walking particles build branching fractal crystals by sticking to a growing aggregate — the mathematics behind snowflakes, lightning, and mineral deposits.

Preset Classic DLA
Stuck  1
Radius 0.0
Walkers 6

Presets

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About DLA

Witten & Sander (1981) model. Fractal dimension D ≈ 1.71 in 2D. Blue = core, red = tips. Symmetry modes impose n-fold mirror axes.

How DLA Works

Algorithm:
1. Place a seed particle at the centre.
2. Launch a new particle at a random point on a circle of radius r_max + δ.
3. The particle performs a random walk (4 directions, equal probability).
4. If the particle wanders too far, kill it and spawn a replacement.
5. When the particle is adjacent to a stuck particle, stick it with probability p (stickiness). p = 1 gives classic DLA; p < 1 gives denser clusters.
6. Increment r_max if the new particle extends the cluster.

Fractal Geometry of the Cluster

A DLA cluster is a fractal: it exhibits self-similar branching at all length scales. The fractal dimension D ≈ 1.71 in 2D, measured by the box-counting or sandbox method. Because D < 2, the cluster occupies a vanishingly small fraction of the enclosing disc as it grows — the tips branch before the interior can fill.

The screening effect drives the branching: a random walker must pass through the outer tips to reach the interior, but the probability of doing so decreases exponentially with depth. Branch tips grow faster than gaps, amplifying any small fluctuation into a permanent branch.

Fractal Dimension

D ≈ 1.71 in 2D (Witten-Sander universality class). N(r) ~ r^D: cluster mass grows sublinearly with radius.

Screening Effect

Outer tips receive far more incoming walkers than interior concavities. Branching is inevitable and self-amplifying.

Stickiness

p=1 → classic sparse DLA (D≈1.71). p→0 → dense Eden model (D→2). Fractal dimension tunes continuously.

Symmetry Modes

Imposing 4-fold or 6-fold symmetry mirrors each stuck particle, creating crystal-like snowflakes.

Real-World Analogues

PhenomenonDLA connectionD (approx.)
Snowflake/ice crystal arms Water vapour diffuses to ice surface — growth limited by diffusion through vapour1.7–1.9
Lightning discharge Charge carries diffuse and discharge channel grows tip-first by dielectric breakdown≈ 1.75
Electrodeposition (zinc) Metal ions diffuse in solution and deposit on electrode tip-first1.66–1.75
Mineral dendrites (manganese) Mineral ions percolate through rock fractures and deposit diffusion-limited patterns≈ 1.7
Viscous fingering (Hele-Shaw) Less-viscous fluid invades more-viscous fluid in porous medium — finger instability≈ 1.7

Curriculum Connections

LevelTopics illustrated
GCSE / A-Level Fractals, random walks, probability, diffusion, crystal growth
IB / A-Level Further Fractal dimension, box-counting, chaos and self-similarity
University Year 1–2 Brownian motion, stochastic processes, Monte Carlo methods, PDE diffusion
Research / Extension DLA universality class, Laplacian growth, harmonic measure, multifractal analysis

Frequently Asked Questions

How long does it take to grow a large DLA cluster?

The growth time scales as N·ln(r_max) because each new particle must perform a random walk of average length proportional to r_max to reach the cluster. The simulation runs multiple walkers in parallel and processes 80 steps per animation frame for speed.

What makes the Snowflake 6× preset different?

The 6-fold symmetry mode mirrors each newly stuck particle to 5 additional positions rotated by 60°, 120°, 180°, 240°, and 300°. This enforces the same hexagonal symmetry as real snowflakes, which grow under the thermodynamic 6-fold symmetry of crystalline ice lattice.

Does upward bias change the fractal dimension?

Yes. Adding a drift velocity breaks the statistical isotropy of the random walk, causing the cluster to grow preferentially upward into a needle-like shape with a fractal dimension closer to 1.0 (a nearly 1D structure). This models directed growth like frost on a cold surface or anisotropic crystal growth.

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