Logarithmic intermittency of the critical 2D SHF

Abstract

While the solution to the $1+1$ dimensional stochastic heat equation with multiplicative noise is closely related to the exponential of a Brownian motion, the two-dimensional picture exhibits an additional weak-to-strong disorder transition. In [CSZ '23], the critical two-dimensional stochastic heat flow (SHF) was constructed as the scaling limit of the partition function of $2+1$ dimensional directed polymers under the logarithmic intermediate-disorder scaling at criticality. The SHF is a random measure and, like many naturally occurring random measures, it is expected to exhibit rich intermittency. [CSZ '25] established that it is almost surely singular with respect to the Lebesgue measure. More recently, [GT '26] showed that the logarithm of the SHF averaged over small balls is asymptotically Gaussian, with both its mean and variance diverging as the ball radius tends to zero. In this paper we prove a sharp result quantifying the singularity of the support of the SHF as well as its intermittency. In particular, we show that, almost surely, for all small $\varepsilon>0$, up to a vanishing error, all the mass of the point-to-plane SHF in any domain is concentrated on ${1}/{\big(\varepsilon^2\log^{1/2+o(1)}(1/\varepsilon)\big)}$ balls of radius $\varepsilon$, each containing $\varepsilon^2{\log^{1/2+o(1)}(1/\varepsilon)}$ mass, thus precisely establishing its logarithmic fractal behavior. A key ingredient in the proof is a refined large-deviations theory, which allows access to conditional distributions, by taking advantage of the Gaussian-like behavior of the SHF at quasi-critical scales. A further useful observation that features prominently is that conditioning a Brownian motion on its endpoint being unusually large essentially induces a shift in the mean of its increments, and consequently, at small enough scales, their distributions do not alter significantly.