The Physics Behind Diffusion Models

Welcome file The Physics Behind Diffusion Models From Brownian motion to Stable Diffusion — how physics shapes the world of generative AI. Introduction Diffusion models have transformed how machines generate images — from creating photorealistic art to driving large-scale creative systems. But beneath all the neural network abstractions lies something beautifully simple and universal: physics. At their core, diffusion models are governed by the laws of stochastic dynamics — the same equations that describe the random motion of particles in fluids. What began as a physical theory of diffusion has evolved into the mathematical backbone of modern generative AI. Let’s begin with the physical world and climb gradually toward the equations that drive Stable Diffusion 3 . 1. Diffusion in the Physical World In the physical world, diffusion describes how particles spread out over time due to random motion — like ink dispersing in water. The key idea is that random...