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Mutualistic networks are used to study the structure and processes inherent to mutualistic relationships. In this paper, we introduce a random matrix ensemble (RME) representing the adjacency matrices of mutualistic networks composed by two…

Disordered Systems and Neural Networks · Physics 2021-11-10 C. T. Martínez-Martínez , J. A. Méndez-Bermúdez , Thomas Peron , Yamir Moreno

Having spectral correlations that, over small enough energy scales, are described by random matrix theory is regarded as the most general defining feature of quantum chaotic systems as it applies in the many-body setting and away from any…

Statistical Mechanics · Physics 2024-09-02 Jonathon Riddell , Curt von Keyserlingk , Tomaž Prosen , Bruno Bertini

We consider perturbations of a large Jordan matrix, either random and small in norm or of small rank. In both cases we show that most of the eigenvalues of the perturbed matrix are very close to a circle with centre at the origin. In the…

Spectral Theory · Mathematics 2007-05-23 E B Davies , Mildred Hager

We investigate the reliability of transition strengths computed in the random-phase approximation (RPA), comparing with exact results from diagonalization in full $0\hbar\omega$ shell-model spaces. The RPA and shell-model results are in…

Nuclear Theory · Physics 2009-11-07 Ionel Stetcu , Calvin W. Johnson

We calculate and verify with simulations the ratio between the average translational and rotational energies of systems with rough, inelastic particles, either forced or freely cooling. The ratio shows non-equipartition of energy. In…

Statistical Mechanics · Physics 2009-10-31 S. McNamara , S. Luding

In order to analyze the effect of chaos or order on the rate of decoherence in a subsystem we aim to distinguish effects of the two types of dynamics from those depending on the choice of the wave packet. To isolate the former we introduce…

Chaotic Dynamics · Physics 2007-05-23 T. Gorin , T. H. Seligman

Random matrix theory is finding an increasing number of applications in the context of information theory and communication systems, especially in studying the properties of complex networks. Such properties include short-term and long-term…

Mathematical Physics · Physics 2015-01-13 Sherif M. Abuelenin , Adel Y. Abul-Magd

We investigate the equilibration of a small isolated quantum system by means of its matrix of asymptotic transition probabilities in a preferential basis. The trace of this matrix is shown to measure the degree of equilibration of the…

Statistical Mechanics · Physics 2016-02-04 J. M. Luck

We use random matrix theory to study the spectrum of random geometric graphs, a fundamental model of spatial networks. Considering ensembles of random geometric graphs we look at short range correlations in the level spacings of the…

Physics and Society · Physics 2017-06-08 Carl P. Dettmann , Orestis Georgiou , Georgie Knight

The spectral form factor of random matrix theory plays a key role in the description of disordered and chaotic quantum systems. While its moments are known to be approximately Gaussian, corrections subleading in the matrix dimension, $D$,…

Quantum Physics · Physics 2026-01-06 Alex Altland , Francisco Divi , Tobias Micklitz , Silvia Pappalardi , Maedeh Rezaei

In this paper, High-dimensional data analysis methods are proposed to deal with random matrix which is composed by the real data from power network before and after the fault. The mean spectral radius (MSR) of non-Hermitian random matrices…

Applications · Statistics 2015-03-31 Y. Cao , L. Cai , C. Qiu , J. Gu , X. He , Q. Ai , Z. Jin

We consider a generalized model of repeated quantum interactions, where a system $\mathcal{H}$ is interacting in a random way with a sequence of independent quantum systems $\mathcal{K}_n, n \geq 1$. Two types of randomness are studied in…

Quantum Physics · Physics 2015-02-12 Ion Nechita , Clément Pellegrini

We report the first experimental realization of pattern formation in a spatially extended nonlinear system when the system is alternated between two states, neither of which exhibits patterning. Dynamical equations modeling the system are…

Pattern Formation and Solitons · Physics 2009-11-11 J. P. Sharpe , P. L. Ramazza , N. Sungar , Karl Saunders

In a statistical analysis in Particle Physics, nuisance parameters can be introduced to take into account various types of systematic uncertainties. The best estimate of such a parameter is often modeled as a Gaussian distributed variable…

Data Analysis, Statistics and Probability · Physics 2019-02-25 Glen Cowan

We study the effects of an arbitrary external perturbation in the statistical properties of the S-matrix of quantum chaotic scattering systems in the limit of isolated resonances. We derive, using supersymmetry, an exact non-perturbative…

Condensed Matter · Physics 2009-10-22 A. M. S. Macedo

In approximate ground states obtained from imaginary-time evolution, the spectrum of the state -- its decomposition into exact energy eigenstates -- falls off exponentially with the energy. Here we consider the energy spectra of approximate…

Strongly Correlated Electrons · Physics 2025-01-22 J. Maxwell Silvester , Giuseppe Carleo , Steven R. White

This paper studies the spectral behavior of large dimensional Chatterjee's rank correlation matrix when observations are independent draws from a high-dimensional random vector with independent continuous components. We show that the…

Statistics Theory · Mathematics 2025-10-09 Zhaorui Dong , Fang Han , Jianfeng Yao

This contribution describes a statistical model for decaying quantum systems (e.g. photo-dissociation or -ionization). It takes the interference between direct and indirect decay processes explicitely into account. The resulting expressions…

Chaotic Dynamics · Physics 2009-11-11 T. Gorin

Random matrix theory successfully connects the structure of interactions of large ecological communities to their ability to respond to perturbations. One of the most debated aspects of this approach is the missing role of population…

Populations and Evolution · Quantitative Biology 2018-09-12 Theo Gibbs , Jacopo Grilli , Tim Rogers , Stefano Allesina

In this work we introduce a new residual for normal linear models that are suitable for situations in which we are dealing with heteroskedasticity of unknown form, they are referred to by principal component analysis (PCA) residuals. These…

Methodology · Statistics 2017-09-01 Andréa V. Rocha , Evelina Shamarova , Alexandre B. Simas