Statistical properties of the Green function in finite size for Anderson Localization models with multifractal eigenvectors

TL;DR

This paper investigates the statistical behavior of the Green function in finite-size Anderson localization models with multifractal eigenvectors, revealing how moments scale with system size and broadening, and identifying different regimes and distributions.

Contribution

It provides a unified analysis of Green function statistics in multifractal Anderson models, including scaling regimes and distributional behaviors, without assuming strong correlations between eigenstate weights.

Findings

Moments governed by anomalous exponents in standard scaling regime

Fréchet distribution describes typical Green function in non-standard regimes

Rare events significantly influence moment scaling in certain regimes

Abstract

For Anderson Localization models with multifractal eigenvectors on disordered samples containing $N$ sites, we analyze in a unified framework the consequences for the statistical properties of the Green function. We focus in particular on the imaginary part of the Green function at coinciding points $G^I_{xx}(E-i \eta)$ and study the scaling with the size $N$ of the moments of arbitrary indices $q$ when the broadening follows the scaling $\eta=\frac{c}{N^{\delta}}$. For the standard scaling regime $\delta=1$, we find in the two limits $c \ll 1$ and $c \gg 1$ that the moments are governed by the anomalous exponents $\Delta(q)$ of individual eigenfunctions, without the assumption of strong correlations between the weights of consecutive eigenstates at the same point. For the non-standard scaling regimes $0<\delta<1$, we obtain that the imaginary Green function follows some Fr\'echet distribution in the typical region, while rare events are important to obtain the scaling of the moments. We describe the application to the case of Gaussian multifractality and to the case of linear multifractality.