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We study the spin transport properties of some disordered spin chains with a special focus on the distribution of the frequency-dependent spin conductivity. In the cases of interest here, the systems are governed by an effectively infinite…

Disordered Systems and Neural Networks · Physics 2024-01-30 L. F. C. Faria , Victor L. Quito , João C. Getelina , José A. Hoyos , E. Miranda

This paper deals with the Braess paradox in quantum transport. The scattering matrix formalism is used to consider a two-parameter family of mesoscopic conductors with the topology of the classical Braess transport network. The study…

Mesoscale and Nanoscale Physics · Physics 2022-06-29 A. D. Lobanov , A. D. Lobanova , A. M. Pupasov-Maksimov

Regularized system identification is the major advance in system identification in the last decade. Although many promising results have been achieved, it is far from complete and there are still many key problems to be solved. One of them…

Systems and Control · Electrical Eng. & Systems 2023-04-05 Yue Ju , Biqiang Mu , Lennart Ljung , Tianshi Chen

We introduce N-parameter perturbation theory as a new tool for the study of non-linear relativistic phenomena. The main ingredient in this formulation is the use of the Baker-Campbell-Hausdorff formula. The associated machinery allows us to…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Carlos F. Sopuerta , Marco Bruni , Leonardo Gualtieri

The quantum state of a light beam can be represented as an infinite dimensional density matrix or equivalently as a density on the plane called the Wigner function. We describe quantum tomography as an inverse statistical problem in which…

Statistics Theory · Mathematics 2007-06-13 L. M. Artiles , R. D. Gill , M. I. Guta

The paper deals with the theoretical analysis of a logistic system composed of at least two elements with distributed parameters. It has been shown that such a system may generate specific oscillations in spite of the fact that the…

Chaotic Dynamics · Physics 2026-02-10 Marek Berezowski , Artur Grabski

We provide and study complete sets of one-loop renormalization group equations of several Finkel'stein non-linear $\sigma$-models, the effective field theories describing the diffusive quantum fluctuations in correlated disordered systems.…

Disordered Systems and Neural Networks · Physics 2017-07-11 Luca Dell'Anna

This article is an introductory review of random matrix theory (RMT) and its applications, with special focus on quantum chaos. Random matrices were first used by Wigner to understand the spectra of complex nuclei from a statistical…

Statistical Mechanics · Physics 2019-05-28 Akhilesh Pandey , Avanish Kumar , Sanjay Puri

Sparse non-Hermitian random matrices arise in the study of disordered physical systems with asymmetric local interactions, and have applications ranging from neural networks to ecosystem dynamics. The spectral characteristics of these…

Statistical Mechanics · Physics 2024-02-21 Fernando Lucas Metz , Izaak Neri , Tim Rogers

We study the random binary contingency tables with non-uniform margin. More precisely, for parameters $n,\delta,B,C$, we consider $X=(X_{ij})$ with $X_{ij}\in \lbrace 0,1\rbrace$, the random binary contingency tables whose first…

Probability · Mathematics 2022-09-19 Da Wu

We present a diagrammatic theory for coherent backscattering from disordered dilute media in the nonlinear regime. The approach is non-perturbative in the strength of the nonlinearity. We show that the coherent backscattering enhancement…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 Thomas Wellens , Benoit Gremaud

Random matrix theory is a powerful tool for understanding spectral correlations inherent in quantum chaotic systems. Despite diverse applications of non-Hermitian random matrix theory, the role of symmetry remains to be fully established.…

Mesoscale and Nanoscale Physics · Physics 2024-07-10 Zhenyu Xiao , Ryuichi Shindou , Kohei Kawabata

Random matrix theory has played a major role in several areas of pure and applied mathematics, as well as statistics, physics, and computer science. This lecture aims to describe the intrinsic freeness phenomenon and how it provides new…

Probability · Mathematics 2025-10-02 Afonso S. Bandeira

Nonlinear instabilities are responsible for spontaneous pattern formation in a vast number of natural and engineered systems ranging from biology to galaxies build-up. We propose a new instability mechanism leading to pattern formation in…

Pattern Formation and Solitons · Physics 2016-01-20 A. M. Perego , N. Tarasov , D. V. Churkin , S. K. Turitsyn , K. Staliunas

We find an analog of Zamolodchikov's c-theorem for disordered two dimensional noninteracting systems in their supersymmetric representation. For this purpose we introduce a new parameter b which flows along the renormalization group…

Disordered Systems and Neural Networks · Physics 2009-10-31 V. Gurarie

The Kumaraswamy distribution has been proposed as an alternative to the beta distribution with more benign algebraic properties. They have the same two parameters, the same support and qualitatively similar shape for any parameter values.…

Statistics Theory · Mathematics 2011-06-21 Baltasar Trancón y Widemann

Generally, natural scientific problems are so complicated that one has to establish some effective perturbation or nonperturbation theories with respect to some associated ideal models. In this Letter, a new theory that combines…

Computational Physics · Physics 2015-05-13 Yuan Gao , S. Y. Lou

The transport coefficients of disordered media are analyzed using direct numerical simulation and effective medium theory. The results indicate a range of materials parameters for which disorder leads to an enhanced power factor. This…

Materials Science · Physics 2015-03-19 Paul M. Haney

We review the author's results on Mather's $\beta$ function : non-strict convexity of $\beta$ when the configuration space has dimension two, link between the size of the Aubry set and the differentiability of $\beta$, correlation between…

Dynamical Systems · Mathematics 2011-02-08 Daniel Massart

The spectra of random feature matrices provide essential information on the conditioning of the linear system used in random feature regression problems and are thus connected to the consistency and generalization of random feature models.…

Machine Learning · Statistics 2022-12-13 Zhijun Chen , Hayden Schaeffer , Rachel Ward