Home▸Networks & Graph Theory▸Scale-Free Network Growth (2D)

🕸️ Scale-Free Network Growth (2D)

A 2D Canvas graph diagram of the Barabási-Albert preferential-attachment model: new nodes join with m edges, chosen with probability proportional to existing degree, growing real power-law hubs. Live degree-distribution exponent estimate.

Networks & Graph Theory2DEasy60 FPS📱 Mobile-adapted⇄ 3D version

⚙ Under the hood

A 2D Canvas graph diagram of the Barabasi-Albert preferential-attachment model: each new node draws m edges chosen with probability proportional to existing node degree, so early well-connected nodes accumulate more links over time. Watch real hubs and a power-law degree distribution emerge live, with a running log-log exponent estimate.

network sciencegraph theorypreferential attachmentpower lawBarabasi-Albert2D

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install