Universal Kardar-Parisi-Zhang fluctuations for moderate deviations of random walks in random environments

The theory of diffusion seeks to describe the motion of particles in a chaotic environment. Classical theory models individual particles as independent random walkers, effectively forgetting that particles evolve together in the same environment. Random walks in a random environment models treat the environment as a random space-time field that biases the motion of particles based on where they are in the environment. We provide a universality result for the moderate deviations of the transition probability of this model over a wide class of choices of random environments. In particular, we show the convergence of moments to those of the multiplicative noise stochastic heat equation, whose logarithm is the Kardar-Parisi-Zhang equation. The environment only filters into the scaling limit through one parameter, which depends explicitly on the statistical description of the environment. This forms the basis for our introduction, in Hass et al. [Phys. Rev. Lett. 133, 267102 (2024)0031-900710.1103/PhysRevLett.133.267102], of the extreme diffusion coefficient.