English

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

Disordered Systems and Neural Networks 2017-02-22 v2

Abstract

For Anderson Localization models with multifractal eigenvectors on disordered samples containing NN 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 GxxI(Eiη)G^I_{xx}(E-i \eta) and study the scaling with the size NN of the moments of arbitrary indices qq when the broadening follows the scaling η=cNδ\eta=\frac{c}{N^{\delta}}. For the standard scaling regime δ=1\delta=1, we find in the two limits c1c \ll 1 and c1c \gg 1 that the moments are governed by the anomalous exponents Δ(q)\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<δ<10<\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.

Keywords

Cite

@article{arxiv.1610.00417,
  title  = {Statistical properties of the Green function in finite size for Anderson Localization models with multifractal eigenvectors},
  author = {Cecile Monthus},
  journal= {arXiv preprint arXiv:1610.00417},
  year   = {2017}
}

Comments

21 pages