A localization-delocalization transition for nonhomogeneous random matrices

Fuente: arXiv
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Main Authors: Shou, Laura, van Handel, Ramon
Format: Preprint
Published: 2023
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author Shou, Laura
van Handel, Ramon
author_facet Shou, Laura
van Handel, Ramon
contents We consider $N\times N$ self-adjoint Gaussian random matrices defined by an arbitrary deterministic sparsity pattern with $d$ nonzero entries per row. We show that such random matrices exhibit a canonical localization-delocalization transition near the edge of the spectrum: when $d\gg\log N$ the random matrix possesses a delocalized approximate top eigenvector, while when $d\ll\log N$ any approximate top eigenvector is localized. The key feature of this phenomenon is that it is universal with respect to the sparsity pattern, in contrast to the delocalization properties of exact eigenvectors which are sensitive to the specific sparsity pattern of the random matrix.
format Preprint
id arxiv_https___arxiv_org_abs_2307_16011
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle A localization-delocalization transition for nonhomogeneous random matrices
Shou, Laura
van Handel, Ramon
Probability
Mathematical Physics
60B20
We consider $N\times N$ self-adjoint Gaussian random matrices defined by an arbitrary deterministic sparsity pattern with $d$ nonzero entries per row. We show that such random matrices exhibit a canonical localization-delocalization transition near the edge of the spectrum: when $d\gg\log N$ the random matrix possesses a delocalized approximate top eigenvector, while when $d\ll\log N$ any approximate top eigenvector is localized. The key feature of this phenomenon is that it is universal with respect to the sparsity pattern, in contrast to the delocalization properties of exact eigenvectors which are sensitive to the specific sparsity pattern of the random matrix.
title A localization-delocalization transition for nonhomogeneous random matrices
topic Probability
Mathematical Physics
60B20
url https://arxiv.org/abs/2307.16011