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Related papers: Complex outliers of Hermitian random matrices

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For fixed positive integers m, we consider the product of m independent n by n random matrices with iid entries as in the limit as n tends to infinity. Under suitable assumptions on the entries of each matrix, it is known that the limiting…

Probability · Mathematics 2017-11-21 Natalie Coston , Sean O'Rourke , Philip Matchett Wood

We study the distribution of the outliers in the spectrum of finite rank deformations of Wigner random matrices. We assume that the matrix entries have finite fourth moment and extend the results by Capitaine, Donati-Martin, and F\'eral for…

Probability · Mathematics 2012-10-24 David Renfrew , Alexander Soshnikov

Consider the matrix $\Sigma_n = n^{-1/2} X_n D_n^{1/2} + P_n$ where the matrix $X_n \in \C^{N\times n}$ has Gaussian standard independent elements, $D_n$ is a deterministic diagonal nonnegative matrix, and $P_n$ is a deterministic matrix…

Probability · Mathematics 2013-01-23 Francois Chapon , Romain Couillet , Walid Hachem , Xavier Mestre

We consider the eigenvalues and eigenvectors of small rank perturbations of random $N\times N$ matrices. We allow the rank of perturbation $M$ increases with $N$, and the only assumption is $M=o(N)$. In both additive and multiplicative…

Probability · Mathematics 2015-05-18 Jiaoyang Huang

A generalized Wigner matrix perturbed by a finite-rank deterministic matrix is considered. The fluctuations of the largest eigenvalues, which emerge outside the bulk of the spectrum, and the corresponding eigenvectors, are studied. Under…

Probability · Mathematics 2026-01-16 Bishakh Bhattacharya , Arijit Chakrabarty , Rajat Subhra Hazra

We study Hermitian random matrix models with an external source matrix which has equispaced eigenvalues, and with an external field such that the limiting mean density of eigenvalues is supported on a single interval as the dimension tends…

Mathematical Physics · Physics 2013-06-25 Tom Claeys , Dong Wang

We investigate traces of powers of random matrices whose distributions are invariant under rotations (with respect to the Hilbert--Schmidt inner product) within a real-linear subspace of the space of $n\times n$ matrices. The matrices we…

Probability · Mathematics 2023-11-30 Elizabeth S. Meckes , Mark W. Meckes

We investigate the decay of spatial correlations of $\mathcal{PT}$-symmetric non-Hermitian one-dimensional models that host higher-order exceptional points. Beyond a certain correlation length, they develop anomalous power-law behavior that…

Mesoscale and Nanoscale Physics · Physics 2023-08-16 Doru Sticlet , Cătălin Paşcu Moca , Balázs Dóra

Consider the random bipartite Erd\H{o}s-R\'{e}nyi graph $\mathbb{G}(n, m, p)$, where each edge with one vertex in $V_{1}=[n]$ and the other vertex in $V_{2} =[m]$ is connected with probability $p$, and $n=\lfloor \gamma m\rfloor$ for a…

Probability · Mathematics 2025-09-03 Ioana Dumitriu , Hai-Xiao Wang , Zhichao Wang , Yizhe Zhu

In this article, a model of random hermitian matrices is considered, in which the measure $\exp(-S)$ contains a general U(N)-invariant potential and an external source term: $S=N\tr(V(M)+MA)$. The generalization of known determinant…

Condensed Matter · Physics 2009-10-30 P. Zinn-Justin

Euclidean embedding from noisy observations containing outlier errors is an important and challenging problem in statistics and machine learning. Many existing methods would struggle with outliers due to a lack of detection ability. In this…

Machine Learning · Statistics 2020-12-24 Qian Zhang , Xinyuan Zhao , Chao Ding

We consider a square random matrix of size N of the form A + Y where A is deterministic and Y has iid entries with variance 1/N. Under mild assumptions, as N grows, the empirical distribution of the eigenvalues of A+Y converges weakly to a…

Probability · Mathematics 2014-11-04 Charles Bordenave , Mireille Capitaine

This study concerns the issue of high dimensional outliers which are challenging to distinguish from inliers due to the special structure of high dimensional space. We introduce a new notion of high dimensional outliers that embraces…

Statistics Theory · Mathematics 2019-09-06 Hyo Young Choi , J. S. Marron

In this paper, we study the eigenvalues and eigenvectors of the spiked invariant multiplicative models when the randomness is from Haar matrices. We establish the limits of the outlier eigenvalues $\widehat{\lambda}_i$ and the generalized…

Probability · Mathematics 2023-02-28 Xiucai Ding , Hong Chang Ji

Toeplitz matrices form a rich class of possibly non-normal matrices whose asymptotic spectral analysis in high dimension is well-understood. The spectra of these matrices are notoriously highly sensitive to small perturbations. In this…

Probability · Mathematics 2024-10-23 Charles Bordenave , François Chapon , Mireille Capitaine

We study finite-rank normal deformations of rotationally invariant non-Hermitian random matrices. Extending the classical Baik-Ben Arous-P\'ech\'e (BBP) framework, we characterize the emergence and fluctuations of outlier eigenvalues in…

Disordered Systems and Neural Networks · Physics 2026-05-15 Pierre Bousseyroux , Marc Potters

We study limit distributions of independent random matrices as well as limit joint distributions of their blocks under normalized partial traces composed with classical expectation. In particular, we are concerned with the ensemble of…

Operator Algebras · Mathematics 2014-07-25 Romuald Lenczewski

Consider an $N\times N$ Toeplitz matrix $T_N$ with symbol ${a }(\lambda) := \sum_{\ell=-d_2}^{d_1} a_\ell \lambda^\ell$, perturbed by an additive noise matrix $N^{-\gamma} E_N$, where the entries of $E_N$ are centered i.i.d.~random…

Probability · Mathematics 2020-07-27 Anirban Basak , Ofer Zeitouni

We investigate the asymptotic behavior of the eigenvalues of spiked perturbations of Wigner matrices when the dimension goes to infinity. The entries of the Hermitian Wigner matrix have a distribution which is symmetric and satisfies a…

Probability · Mathematics 2011-09-19 Mireille Capitaine , Catherine Donati-Martin , Delphine Féral , Maxime Février

Outlier detection is a major topic in robust statistics due to the high practical significance of anomalous observations. Many existing methods are, however, either parametric or cease to perform well when the data is far from linearly…

Methodology · Statistics 2018-11-14 Matias Heikkilä