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This paper derives exponential tail bounds and polynomial moment inequalities for the spectral norm deviation of a random matrix from its mean value. The argument depends on a matrix extension of Stein's method of exchangeable pairs for…

Probability · Mathematics 2013-05-06 Daniel Paulin , Lester Mackey , Joel A. Tropp

We consider a noninteracting disordered system designed to model particle diffusion, relaxation in glasses, and impurity bands of semiconductors. Disorder originates in the random spatial distribution of sites. We find strong numerical…

Disordered Systems and Neural Networks · Physics 2015-03-17 Jacob J. Krich , Alán Aspuru-Guzik

Two-dimensional networks of ordered quantum dots beyond the percolation threshold are studied, as typical example of conducting nanostructures with quenched random disorder. Theory predicts anomalous diffusion with stretched-exponential…

Statistical Mechanics · Physics 2016-01-06 Fabrizio Cleri

The dynamics of two-dimensional fluids confined within a random matrix of obstacles is investigated using both colloidal model experiments and molecular dynamics simulations. By varying fluid and matrix area fractions in the experiment, we…

Using the supersymmetry method we analytically calculate the local density of states, the localiztion length, the generalized inverse participation ratios, and the distribution function of eigenvector components for the superposition of a…

Condensed Matter · Physics 2009-10-28 Klaus Frahm , Axel Müller--Groeling

Diffusion models have shown remarkable empirical success in sampling from rich multi-modal distributions. Their inference relies on numerically solving a certain differential equation. This differential equation cannot be solved in closed…

Machine Learning · Computer Science 2026-01-16 Khashayar Gatmiry , Sitan Chen , Adil Salim

We analyze gene co-expression network under the random matrix theory framework. The nearest neighbor spacing distribution of the adjacency matrix of this network follows Gaussian orthogonal statistics of random matrix theory (RMT). Spectral…

Molecular Networks · Quantitative Biology 2015-05-18 Sarika Jalan , Norbert Solymosi , Gabör Vattay , Baowen Li

The random banded matrices (RBM) whose diagonal elements fluctuate much stronger than the off-diagonal ones were introduced recently by Shepelyansky as a convenient model for coherent propagation of two interacting particles in a random…

Condensed Matter · Physics 2009-10-28 Yan V. Fyodorov , Alexander D. Mirlin

We review recent progress in analysing wave scattering in systems with both intrinsic chaos and/or disorder and internal losses, when the scattering matrix is no longer unitary. By mapping the problem onto a nonlinear supersymmetric…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Y. V. Fyodorov , D. V. Savin , H. -J. Sommers

In this paper we theoretically study electromagnetic reflection, transmission, and scattering properties of periodic and random arrays of particles which exhibit both electric-mode and magnetic-mode resonances. We compare the properties of…

Materials Science · Physics 2015-06-03 M. Albooyeh , D. Morits , S. A. Tretyakov

Over the past decades, a great body of theoretical and mathematical work has been devoted to random-matrix descriptions of open quantum systems. In these notes, based on lectures delivered at the Les Houches Summer School "Stochastic…

Disordered Systems and Neural Networks · Physics 2017-01-09 Henning Schomerus

Several applications of the moment method in random matrix theory, especially, to local eigenvalue statistics at the spectral edges, are surveyed, with emphasis on a modification of the method involving orthogonal polynomials.

Classical Analysis and ODEs · Mathematics 2014-06-16 Sasha Sodin

Random feature maps are ubiquitous in modern statistical machine learning, where they generalize random projections by means of powerful, yet often difficult to analyze nonlinear operators. In this paper, we leverage the "concentration"…

Machine Learning · Statistics 2021-03-18 Zhenyu Liao , Romain Couillet

We carry out a numerical study of fluctuations in the spectrum of regular graphs. Our experiments indicate that the level spacing distribution of a generic k-regular graph approaches that of the Gaussian Orthogonal Ensemble of random matrix…

High Energy Physics - Theory · Physics 2007-05-23 D. Jakobson , S. D. Miller , I. Rivin , Z. Rudnick

The diffusion model is used to calculate the time-averaged flow of particles in stochastic media and the propagation of waves averaged over ensembles of disordered static configurations. For classical waves exciting static disordered…

Disordered Systems and Neural Networks · Physics 2024-01-11 Azriel Z. Genack , Yiming Huang , Asher Maor , Zhou Shi

We show that the distribution of elements $H$ in the Hessian matrices associated with amorphous materials exhibit singularities $P(H) \sim {\lvert H \rvert}^{\gamma}$ with an exponent $\gamma < 0$, as $\lvert H \rvert \to 0$. We exploit the…

Disordered Systems and Neural Networks · Physics 2020-11-06 Vishnu V. Krishnan , Smarajit Karmakar , Kabir Ramola

This work analyzes the scattering resonances of general acoustic media in a one-dimensional setting using the propagation matrix approach. Specifically, we characterize the resonant frequencies as the zeros of an explicit trigonometric…

Analysis of PDEs · Mathematics 2025-12-02 Yi Huang , Bowen Li , Ping Liu , Yingjie Shao

There has been much recent interest, initiated by work of the physicists Hatano and Nelson, in the eigenvalues of certain random non-Hermitian periodic tridiagonal matrices and their bidiagonal limits. These eigenvalues cluster along a…

Statistical Mechanics · Physics 2007-05-23 Lloyd N. Trefethen , Marco Contedini , Mark Embree

The concept of random walk, in which particles or waves undergo multiple collisions with the microscopic constituents of a surrounding medium, is central to understanding diffusive transport across many research areas. However, this…

In this paper, we use recent breakthroughs in the study of coupled subwavelength resonator systems to reveal new insight into the mechanisms responsible for the fundamental features of Anderson localization. The occurrence strong…

Disordered Systems and Neural Networks · Physics 2023-07-21 Habib Ammari , Bryn Davies , Erik Orvehed Hiltunen
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