Random matrix representations of critical statistics

Author(s):  
Alexei Borodin

This article examines two random matrix ensembles that are useful for describing critical spectral statistics in systems with multifractal eigenfunction statistics: the Gaussian non-invariant ensemble and the invariant random matrix ensemble. It first provides an overview of non-invariant Gaussian random matrix theory (RMT) with multifractal eigenvectors and invariant random matrix theory (RMT) with log-square confinement before discussing self-unfolding and not self-unfolding in invariant RMT. It then considers a non-trivial unfolding and how it changes the form of the spectral correlations, along with the appearance of a ghost correlation dip in RMT and Hawking radiation. It also describes the correspondence between invariant and non-invariant ensembles and concludes by introducing a simple field theory in 1+1 dimensions which reproduces level statistics of both of the two random matrix models and the classical Wigner-Dyson spectral statistics in the framework of the unified formalism of Luttinger liquid.

2022 ◽  
Author(s):  
Hui Jiang ◽  
Ching Hua Lee

Abstract Eigenspectra that fill regions in the complex plane have been intriguing to many, inspiring research from random matrix theory to esoteric semi-infinite bounded non-Hermitian lattices. In this work, we propose a simple and robust ansatz for constructing models whose eigenspectra fill up generic prescribed regions. Our approach utilizes specially designed non-Hermitian random couplings that allow the co-existence of eigenstates with a continuum of localization lengths, mathematically emulating the effects of semi-infinite boundaries. While some of these couplings are necessarily long-ranged, they are still far more local than what is possible with known random matrix ensembles. Our ansatz can be feasibly implemented in physical platforms such as classical and quantum circuits, and harbors very high tolerance to imperfections due to its stochastic nature.


2018 ◽  
Vol 26 (01) ◽  
pp. 1850002 ◽  
Author(s):  
Denis Makarov

Problem of long-range sound propagation in the randomly-inhomogeneous deep ocean is considered. We examine a novel approach for modeling of wave propagation, developed by Hegewisch and Tomsovic. This approach relies on construction of a wavefield propagator using the random matrix theory (RMT). We study the ability of the RMT-based propagator to reproduce properties of the propagator corresponding to direct numerical solution of the parabolic equation. It is shown that mode coupling described by the RMT-based propagator is basically consistent with the direct Monte-Carlo simulation. The agreement is worsened only for relatively short distances, when long-lasting cross-mode correlations are significant. It is shown that the RMT-based propagator with properly chosen range step can reproduce some coherent features in spectral statistics.


1995 ◽  
Vol 75 (5) ◽  
pp. 902-905 ◽  
Author(s):  
A. V. Andreev ◽  
B. L. Altshuler

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