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Within random matrix theory for quantum dots, both the dot's one-particle eigenlevels and the dot-lead couplings are statistically distributed. While the effect of the latter on the conductance is obvious and has been taken into account in…

Mesoscale and Nanoscale Physics · Physics 2009-11-07 K. Held , E. Eisenberg , B. L. Altshuler

We study the spectrum of a random matrix, whose elements depend on the Euclidean distance between points randomly distributed in space. This problem is widely studied in the context of the Instantaneous Normal Modes of fluids and is…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. Mezard , G. Parisi , A. Zee

Atmospheric models used for weather and climate prediction are traditionally formulated in a deterministic manner. In other words, given a particular state of the resolved scale variables, the most likely forcing from the sub-grid scale…

Machine Learning · Computer Science 2024-02-16 Hannah M. Christensen , Salah Kouhen , Greta Miller , Raghul Parthipan

We review our recent results on pseudo-hermitian random matrix theory which were hitherto presented in various conferences and talks. (Detailed accounts of our work will appear soon in separate publications.) Following an introduction of…

Mathematical Physics · Physics 2021-10-27 Joshua Feinberg , Roman Riser

We study random points on the real line generated by the eigenvalues in unitary invariant random matrix ensembles or by more general repulsive particle systems. As the number of points tends to infinity, we prove convergence of the…

Probability · Mathematics 2015-11-11 Kristina Schubert , Martin Venker

Random matrix theory is used to represent generic loss of coherence of a fixed central system coupled to a quantum-chaotic environment, represented by a random matrix ensemble, via random interactions. We study the average density matrix…

Quantum Physics · Physics 2009-09-30 T. Gorin , C. Pineda , H. Kohler , T. H. Seligman

Measurements on a single quantum system at different times reveal rich non-classical correlations similar to those observed in spatially separated multi-partite systems. Here we introduce a theory framework that unifies the description of…

Quantum Physics · Physics 2018-08-01 Fabio Costa , Martin Ringbauer , Michael E. Goggin , Andrew G. White , Alessandro Fedrizzi

We provide a perturbative expansion for the empirical spectral distribution of a Hermitian matrix with large size perturbed by a random matrix with small operator norm whose entries in the eigenvector basis of the first one are independent…

Probability · Mathematics 2017-10-03 Florent Benaych-Georges , Nathanaël Enriquez , Alkéos Michaïl

A density matrix formulation of classical bipartite correlations is constructed. This leads to an understanding of the appearance of classical statistical correlations intertwined with the quantum correlations as well as a physical…

Quantum Physics · Physics 2009-11-11 A. K. Rajagopal , R. W. Rendell

Non-asymptotic theory of random matrices strives to investigate the spectral properties of random matrices, which are valid with high probability for matrices of a large fixed size. Results obtained in this framework find their applications…

Probability · Mathematics 2013-08-02 Mark Rudelson

We show that the averaged characteristic polynomial and the averaged inverse characteristic polynomial, associated with Hermitian matrices whose elements perform a random walk in the space of complex numbers, satisfy certain partial…

Mathematical Physics · Physics 2015-12-22 Jean-Paul Blaizot , Jacek Grela , Maciej A. Nowak , Piotr Warchoł

What is the connection of random matrices with integrable systems? Is this connection really useful? Introducing apprpriate times in the distribution of the ensemble of matrices, one shows that the corresponding distribution of the…

solv-int · Physics 2008-02-03 Pierre van Moerbeke

We show that correlation matrices with particular average and variance of the correlation coefficients have a notably restricted spectral structure. Applying geometric methods, we derive lower bounds for the largest eigenvalue and the…

Mathematical Physics · Physics 2021-08-25 Yuriy Stepanov , Hendrik Herrmann , Thomas Guhr

Using the superstatistics method, we propose an extension of the random matrix theory to cover systems with mixed regular-chaotic dynamics. Unlike most of the other works in this direction, the ensembles of the proposed approach are basis…

Statistical Mechanics · Physics 2007-05-23 A. Y. Abul-Magd

We introduce a family of random matrices where correlations between matrix elements are induced via interaction-derived Boltzmann factors. Varying these yields access to different ensembles. We find a universal scaling behavior of the…

Statistical Mechanics · Physics 2025-03-06 Abbas Ali Saberi , Sina Saber , Roderich Moessner

Quantum statistical correlations and momentum distributions are calculated for a spherically symmetric, three-dimensionally expanding finite fireballs, for non-relativistic expansions applying plane-wave approximation. The new concepts of…

Nuclear Theory · Physics 2010-11-19 T. Csorgo B. Lorstad , J. Zimanyi

Complex extension of quantum mechanics and the discovery of pseudo-unitarily invariant random matrix theory has set the stage for a number of applications of these concepts in physics. We briefly review the basic ideas and present…

Quantum Physics · Physics 2013-02-13 Shashi. C. L. Srivastava , S. R. Jain

The effective Hamiltonian formalism is extended to vectorial electromagnetic waves in order to describe statistical properties of the field in reverberation chambers. The latter are commonly used in electromagnetic compatibility tests. As a…

Mesoscale and Nanoscale Physics · Physics 2016-03-09 J. -B. Gros , U. Kuhl , O. Legrand , F. Mortessagne

We develop a supersymmetric field theoretical description of the Gaussian ensemble of the almost diagonal Hermitian Random Matrices. The matrices have independent random entries H_{ij} with parametrically small off-diagonal elements…

Disordered Systems and Neural Networks · Physics 2016-09-07 Oleg Yevtushenko , Alexander Ossipov

Identifying an appropriate covariance function is one of the primary interests in spatial and spatio-temporal statistics because it allows researchers to analyze the dependence structure of the random process. For this purpose, spatial…

Methodology · Statistics 2025-02-04 Jongwook Kim , Chunfeng Huang , Nicholas Bussberg
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