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arxiv: 1511.02718 · v2 · pith:ICKZSXD7new · submitted 2015-11-09 · 🧮 math.PR

The continuous Anderson hamiltonian in dimension two

classification 🧮 math.PR
keywords operatormathbbmathscrvarepsilondeltagaussiannoisepotential
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We define the Anderson hamiltonian on the two dimensional torus $\mathbb R^2/\mathbb Z^2$. This operator is formally defined as $\mathscr H:= -\Delta + \xi$ where $\Delta$ is the Laplacian operator and where $\xi$ belongs to a general class of singular potential which includes the Gaussian white noise distribution. We use the notion of paracontrolled distribution as introduced by Gubinelli, Imkeller and Perkowski in [14]. We are able to define the Schr\"odinger operator $\mathscr H$ as an unbounded self-adjoint operator on $L^2(\mathbb T^2)$ and we prove that its real spectrum is discrete with no accumulation points for a general class of singular potential $\xi$. We also establish that the spectrum is a continuous function of a sort of enhancement $\Xi(\xi)$ of the potential $\xi$. As an application, we prove that a correctly renormalized smooth approximations $\mathscr H_\varepsilon:= -\Delta + \xi_\varepsilon+c_\varepsilon$ (where $\xi_\varepsilon$ is a smooth mollification of the Gaussian white noise $\xi$ and $c_\varepsilon$ an explicit diverging renormalization constant) converge in the sense of the resolvent towards the singular operator $\mathscr H$. In the case of a Gaussian white noise $\xi$, we obtain exponential tail bounds for the minimal eigenvalue (sometimes called ground state) of the operator $\mathscr H$ as well as its order of magnitude $\log L$ when the operator is considered on a large box $\mathbb T_L:= \mathbb R^2/(L\mathbb Z)^2$ with $L\to \infty$.

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