Construction and spectrum of the Anderson Hamiltonian with white noise potential on $\mathbf{R}^2$ and $\mathbf{R}^3$
Yueh-Sheng Hsu, Cyril Labbé
TL;DR
This work provides a rigorous construction of the Anderson Hamiltonian $\mathcal{H}=-\Delta+\xi$ with white-noise potential on $\mathbb{R}^2$ and $\mathbb{R}^3$ by leveraging the parabolic Anderson model and a Klein–Landau semigroup framework. It renormalizes the ill-defined distributional potential, builds the PAM semigroup, and obtains a self-adjoint generator as the strong resolvent limit of renormalized operators; in 2D and 3D, it is shown that the spectrum is almost surely the entire real line. The analysis hinges on enhanced noise spaces for PAM in 2D, and regularity-structures techniques for PAM in 3D, together with a Kotani-type argument that transfers Weyl-sequence reasoning to the singular setting. The results offer a robust, broadly applicable methodology for singular random differential operators beyond the present model, with implications for spectral theory and stochastic PDE renormalization.
Abstract
We propose a simple construction of the Anderson Hamiltonian with white noise potential on $\mathbf{R}^2$ and $\mathbf{R}^3$ based on the solution theory of the parabolic Anderson model. It relies on a theorem of Klein and Landau [KL81] that associates a unique self-adjoint generator to a symmetric semigroup satisfying some mild assumptions. Then, we show that almost surely the spectrum of this random Schrödinger operator is $\mathbf{R}$. To prove this result, we extend the method of Kotani [Kot85] to our setting of singular random operators.
