English

Multifractality and statistical localization in highly heterogeneous random networks

Disordered Systems and Neural Networks 2023-11-29 v1 Statistical Mechanics Probability

Abstract

We consider highly heterogeneous random networks with symmetric interactions in the limit of high connectivity. A key feature of this system is that the spectral density of the corresponding ensemble exhibits a divergence within the bulk. We study the structure of the eigenvectors associated with this divergence and find that they are multifractal with the statistics of eigenvector elements matching those of the resolvent entries. The corresponding localization mechanism relies on the statistical properties of the nodes rather than on any spatial structure around a localization centre. This "statistical localization" mechanism is potentially relevant for explaining localization in different models that display singularities in the bulk of the spectrum of eigenvalues

Keywords

Cite

@article{arxiv.2311.15808,
  title  = {Multifractality and statistical localization in highly heterogeneous random networks},
  author = {Diego Tapias and Peter Sollich},
  journal= {arXiv preprint arXiv:2311.15808},
  year   = {2023}
}

Comments

Accepted for publication in Europhysics Letters (EPL)

R2 v1 2026-06-28T13:32:39.357Z