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Fractal geometry of the PAM in 2D and 3D with white noise potential
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abstract
We study the parabolic Anderson model (PAM) \begin{equation} {\partial \over \partial t}u(t,x) =\frac{1}{2}\Delta u(t,x) + u(t,x)\xi(x), \quad t>0, x\in \mathbb{R}^d, \quad \text{and} \quad u(0,x) \equiv 1, \quad \forall x\in \mathbb{R}^d, \end{equation} where $\xi$ is spatial white noise on $\mathbb{R}^d$ with $d \in\{2,3\}$. We show that the peaks of the PAM are macroscopically multifractal. More precisely, we prove that the spatial peaks of the PAM have infinitely many distinct values and we compute the macroscopic Hausdorff dimension (introduced by Barlow and Taylor) of those peaks. As a byproduct, we obtain the exact spatial asymptotics of the solution of the PAM. We also study the spatio-temporal peaks of the PAM and show their macroscopic multifractality. Some of the major tools used in our proof techniques include paracontrolled calculus and tail probabilities of the largest point in the spectrum of the Anderson Hamiltonian.
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Sharp moment and upper tail asymptotics for the critical $2d$ Stochastic Heat Flow
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