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We consider the eigenvalues and eigenvectors of finite, low rank perturbations of random matrices. Specifically, we prove almost sure convergence of the extreme eigenvalues and appropriate projections of the corresponding eigenvectors of…

Probability · Mathematics 2012-03-19 Florent Benaych-Georges , Raj Rao Nadakuditi

Investigating the microscopic details of the proximity effect is crucial for both key experimental applications and fundamental inquiries into nanoscale devices featuring superconducting elements. In this work, we develop a framework…

Mesoscale and Nanoscale Physics · Physics 2024-12-11 Siddhant Midha , Roshni Singh , Kaveh Gharavi , Jonathan Baugh , Bhaskaran Muralidharan

We study a two-dimensional system of two Coulombically interacting electrons in an external harmonic confining potential. More precisely, we present calculations for the singlet ground-state of the system. We explain the nature of the…

Quantum Physics · Physics 2017-07-17 Przemyslaw Koscik

We derive the exact form of the eigenvalue spectra of correlation matrices derived from a set of time-shifted, finite Brownian random walks (time-series). These matrices can be seen as random, real, asymmetric matrices with a special…

Physics and Society · Physics 2008-12-02 Christoly Biely , Stefan Thurner

Statistical properties of eigenvectors in non-Hermitian random matrix ensembles are discussed, with an emphasis on correlations between left and right eigenvectors. Two approaches are described. One is an exact calculation for Ginibre's…

Disordered Systems and Neural Networks · Physics 2015-06-25 B. Mehlig , J. T. Chalker

Cross-Correlation random matrices have emerged as a promising indicator of phase transitions in spin systems. The core concept is that the evolution of magnetization encapsulates thermodynamic information [R. da Silva, Int. J. Mod. Phys. C,…

Statistical Mechanics · Physics 2024-08-19 Roberto da Silva , Sandra D. Prado

We characterize the eigenvalues and eigenvectors of a class of complex valued tridiagonal $n$ by $n$ matrices subject to arbitrary boundary conditions, i.e. with arbitrary elements on the first and last rows of the matrix. %By boundary…

Numerical Analysis · Mathematics 2018-01-17 J. J. P. Veerman , D. K. Hammond , Pablo E. Baldivieso

We derive variational equations to analyze the stability of synchronization for coupled near-identical oscillators. To study the effect of parameter mismatch on the stability in a general fashion, we define master stability equations and…

Chaotic Dynamics · Physics 2015-05-13 Jie Sun , Erik M. Bollt , Takashi Nishikawa

The effects of short-range correlations derived from a realistic meson-exchange potential on the single-particle density matrix in finite nuclei are investigated by analyzing the one-body density in terms of the natural orbits. Basic…

Nuclear Theory · Physics 2016-09-08 A. Polls , H. Müther , W. H. Dickhoff

Correlation function of complex eigenvalues of N by N random matrices drawn from non-Hermitean random matrix ensemble of symplectic symmetry is given in terms of a quaternion determinant. Spectral properties of Gaussian ensembles are…

Statistical Mechanics · Physics 2009-11-07 E. Kanzieper

A density functional theory for many-body lattice models is considered in which the single-particle density matrix is the basic variable. Eigenvalue equations are derived for solving Levy's constrained search of the interaction energy…

Strongly Correlated Electrons · Physics 2009-10-31 R. Lopez-Sandoval , G. M. Pastor

Disorder-induced spectral correlations of mesoscopic quantum systems in the non-diffusive regime and their effect on the magnetic susceptibility are studied. We perform impurity averaging for non-translational invariant systems by combining…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 Edward McCann , Klaus Richter

We consider a class of sparse random matrices, which includes the adjacency matrix of Erd\H{o}s-R\'enyi graphs $\mathcal G(N,p)$ for $p \in [N^{\varepsilon-1},N^{-\varepsilon}]$. We identify the joint limiting distributions of the…

Probability · Mathematics 2020-03-13 Yukun He

Correlations of eigenfunctions, $\langle|\psi_k(r_1)|^2|\psi_l(r_2)|^2\rangle$, in a disordered system are investigated. We derive general formulae expressing these correlation functions in terms of the supermatrix sigma-model. In…

Condensed Matter · Physics 2009-10-28 Ya. M. Blanter , A. D. Mirlin

Random contractions (sub-unitary random matrices) appear naturally when considering quantized chaotic maps within a general theory of open linear stationary systems with discrete time. We analyze statistical properties of complex…

Chaotic Dynamics · Physics 2009-10-31 Yan V. Fyodorov , H. -J. Sommmers

We show that results from the theory of random matrices are potentially of great interest to understand the statistical structure of the empirical correlation matrices appearing in the study of price fluctuations. The central result of the…

Condensed Matter · Physics 2009-10-31 Laurent Laloux , Pierre Cizeau , Jean-Philippe Bouchaud , Marc Potters

Random Hermitian matrices are used to model complex systems without time-reversal invariance. Adding an external source to the model can have the effect of shifting some of the matrix eigenvalues, which corresponds to shifting some of the…

Mathematical Physics · Physics 2015-05-20 Marco Bertola , Robert Buckingham , Seung-Yeop Lee , Virgil U. Pierce

Using a nonperturbative approach we examine the large frequency asymptotics of the two-point level density correlator in weakly disordered metallic grains. This allows us to study the behavior of the two-level structure factor close to the…

Condensed Matter · Physics 2016-08-31 A. V. Andreev , B. L. Altshuler

Quantum-statistical correlation measurements in high-energy physics represent an important tool to obtain information about the space-time structure of the particle-emitting source. There are several final state effects which may modify the…

High Energy Physics - Phenomenology · Physics 2023-09-27 Mate Csanad , Antal Jakovac , Sandor Lokos , Ayon Mukherjee , Srikanta Kumar Tripathy

This paper examines the relationship between sparse random network architectures and neural network stability by examining the eigenvalue spectral distribution. Specifically, we generalise classical eigenspectral results to sparse…

Neurons and Cognition · Quantitative Biology 2023-10-12 Isabelle D Harris , Hamish Meffin , Anthony N Burkitt , Andre D. H Peterson
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