English
Related papers

Related papers: Eigenvalue processes of symmetric tridiagonal matr…

200 papers

We consider a stochastic process $Y$ defined by an integral in quadratic mean of a deterministic function $f$ with respect to a Gaussian process $X$, which need not have stationary increments. For a class of Gaussian processes $X$, it is…

Probability · Mathematics 2015-06-01 Rimas Norvaiša

We investigate eigenvalues of many-body systems interacting by two-body forces as well as those of random matrices. We find a strong linear correlation between eigenvalues and diagonal matrix elements if both of them are sorted from the…

Nuclear Theory · Physics 2008-11-26 J. J. Shen , A. Arima , Y. M. Zhao , N. Yoshinaga

We introduce the concept of theta-antieigenvalue and theta-antieigenvector of a bounded linear operator on complex Hilbert space. We study the relation between theta-antieigenvalue and centre of mass of a bounded linear operator and compute…

Functional Analysis · Mathematics 2024-07-30 Kallol Paul , Gopal Das , Lokenath Debnath

We propose a new method for computing the eigenvalue decomposition of a dense real normal matrix $A$ through the decomposition of its skew-symmetric part. The method relies on algorithms that are known to be efficiently implemented, such as…

Numerical Analysis · Mathematics 2026-03-31 Simon Mataigne , Kyle A. Gallivan

We consider random non-normal matrices constructed by removing one row and column from samples from Dyson's circular ensembles or samples from the classical compact groups. We develop sparse matrix models whose spectral measures match these…

Probability · Mathematics 2016-06-22 Rowan Killip , Rostyslav Kozhan

We introduce a general method for transforming the equations of motion following from a Das-Jevicki-Sakita Hamiltonian, with boundary conditions, into a boundary value problem in one-dimensional quantum mechanics. For the particular case of…

High Energy Physics - Theory · Physics 2009-10-31 L. D. Paniak

We prove large deviation principles for $\int_0^t \gamma(X_s)ds$, where $X$ is a $d$-dimensional self-similar Gaussian process and $\gamma(x)$ takes the form of the Dirac delta function $\delta(x)$, $|x|^{-\beta}$ with $\beta\in (0,d)$, or…

Probability · Mathematics 2020-01-22 Xiaoming Song

We consider pairs of GOE (Gaussian Orthogonal Ensemble) matrices which are correlated with each others, and subject to additive and multiplicative rank-one perturbations. We focus on the regime of parameters in which the finite-rank…

Disordered Systems and Neural Networks · Physics 2023-09-15 Alessandro Pacco , Valentina Ros

We study the boundary symmetries of models of nonequilibrium physics where the steady state behaviour strongly depends on the boundary rates. Within the matrix product state approach to many-body systems the physics is described in terms of…

Mathematical Physics · Physics 2008-07-29 Boyka Aneva

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

We study Bessel processes on Weyl chambers of types A and B on $\mathbb R^N$. Using elementary symmetric functions, we present several space-time-harmonic functions and thus martingales for these processes $(X_t)_{t\ge0}$ which are…

Probability · Mathematics 2019-08-30 Miklos Kornyik , Michael Voit , Jeannette H. C. Woerner

We prove that the linear statistics of the eigenvalues of a Wigner matrix converge to a universal Gaussian process on all mesoscopic spectral scales, i.e. scales larger than the typical eigenvalue spacing and smaller than the global extent…

Probability · Mathematics 2018-03-29 Yukun He , Antti Knowles

We compute analytically the probability density function (pdf) of the largest eigenvalue $\lambda_{\max}$ in rotationally invariant Cauchy ensembles of $N\times N$ matrices. We consider unitary ($\beta = 2$), orthogonal ($\beta =1$) and…

Statistical Mechanics · Physics 2013-01-29 Satya N. Majumdar , Gregory Schehr , Dario Villamaina , Pierpaolo Vivo

We establish a correspondence between the evolution of the distribution of eigenvalues of a $N\times N$ matrix subject to a random Gaussian perturbing matrix, and a Fokker-Planck equation postulated by Dyson. Within this model, we prove the…

Condensed Matter · Physics 2009-10-22 Onuttom Narayan , B. Sriram Shastry

We introduce a stochastic process and functional that should describe the semigroup generated by the stochastic Bessel operator. Recently Gorin and Shkolnikov showed that the largest eigenvalues for certain random matrix ensembles with soft…

Probability · Mathematics 2017-11-06 Patrick Waters

Parameter identification and comparison of dynamical systems is a challenging task in many fields. Bayesian approaches based on Gaussian process regression over time-series data have been successfully applied to infer the parameters of a…

Machine Learning · Statistics 2019-03-04 Philippe Wenk , Alkis Gotovos , Stefan Bauer , Nico Gorbach , Andreas Krause , Joachim M. Buhmann

We study estimation and prediction of Gaussian processes with covariance model belonging to the generalized Cauchy (GC) family, under fixed domain asymptotics. Gaussian processes with this kind of covariance function provide separate…

Methodology · Statistics 2019-07-23 Moreno Bevilacqua , Tarik Faouzi

The quantum eigenvalue problem arises in the study of the geometric measure of the quantum entanglement. In this paper, we convert the quantum eigenvalue problem to the Z-eigenvalue problem of a real symmetric tensor. In this way, the…

Spectral Theory · Mathematics 2012-05-08 Xinzhen Zhang , Liqun Qi

We consider path-connected sets of matrices and the induced paths between eigenvalues. We discuss the equivalence relation generated by these paths, and how it relates to the presence of higher multiplicity eigenvalues realized by the set.…

Mathematical Physics · Physics 2020-10-01 Alex Kokot , Charles Johnson

In this paper, we consider a stochastic system described by a differential equation admitting a spatially varying random coefficient. The differential equation has been employed to model various static physics systems such as elastic…

Probability · Mathematics 2013-09-18 Jingchen Liu , Xiang Zhou
‹ Prev 1 8 9 10 Next ›