Quantum diffusion of the random Schrodinger evolution in the scaling limit

TL;DR

This paper proves that, under a specific scaling limit, the expectation of the Wigner distribution for solutions to a random Schrödinger equation converges to a heat equation, demonstrating quantum diffusion in a rigorous mathematical framework.

Contribution

It provides the first rigorous proof that non-ladder Feynman graphs are suppressed by a power of the small parameter, enabling convergence of the perturbation series in quantum diffusion analysis.

Findings

Expectation of Wigner distribution converges to heat equation solution.

Non-ladder diagram amplitudes are smaller than naive estimates by a power of the small parameter.

Established convergence of the perturbation series for the quantum diffusion problem.

Abstract

We consider random Schr\"odinger equations on $\bR^d$ for $d\ge 3$ with a homogeneous Anderson-Poisson type random potential. Denote by $\lambda$ the coupling constant and $\psi_t$ the solution with initial data $\psi_0$. The space and time variables scale as $x\sim \lambda^{-2 -\kappa/2}, t \sim \lambda^{-2 -\kappa}$ with $0< \kappa < \kappa_0(d)$. We prove that, in the limit $\lambda \to 0$, the expectation of the Wigner distribution of $\psi_t$ converges weakly to the solution of a heat equation in the space variable $x$ for arbitrary $L^2$ initial data. The proof is based on analyzing the phase cancellations of multiple scatterings on the random potential by expanding the propagator into a sum of Feynman graphs. In this paper we consider the non-recollision graphs and prove that the amplitude of the {\it non-ladder} diagrams is smaller than their "naive size" by an extra $\lambda^c$ factor {\em per non-(anti)ladder vertex} for some $c > 0$. This is the first rigorous result showing that the improvement over the naive estimates on the Feynman graphs grows as a power of the small parameter with the exponent depending linearly on the number of vertices. This estimate allows us to prove the convergence of the perturbation series.