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Eigenvalue and eigenvector perturbation theory is a fundamental topic in several disciplines, including numerical linear algebra, quantum physics, and related fields. The central problem is to understand how the eigenvalues and eigenvectors…

Numerical Analysis · Mathematics 2026-02-26 Francesco Hrobat , Yuji Nakatsukasa

We consider eigenvectors of the Hamiltonian $H_0$ perturbed by a generic perturbation $V$ modelled by a random matrix from the Gaussian Unitary Ensemble (GUE). Using the supersymmetry approach we derive analytical results for the statistics…

Disordered Systems and Neural Networks · Physics 2017-01-04 Kevin Truong , Alexander Ossipov

Characterizing the asymptotic distributions of eigenvectors for large random matrices poses important challenges yet can provide useful insights into a range of statistical applications. To this end, in this paper we introduce a general…

Statistics Theory · Mathematics 2020-10-14 Jianqing Fan , Yingying Fan , Xiao Han , Jinchi Lv

While perturbation theories constitute a significant foundation of modern quantum system analysis, extending them from the Hermitian to the non-Hermitian regime remains a non-trivial task. In this work, we generalize the…

Quantum Physics · Physics 2025-11-18 Wei-Ming Chen , Yen-Ting Lin , Chia-Yi Ju

Let A and E be Hermitian self-adjoint matrices, where A is fixed and E a small perturbation. We study how the eigenvalues and eigenvectors of A+E depend on E, with the aim of obtaining first order formulas (and when possible also second…

Mathematical Physics · Physics 2019-08-26 Marcus Carlsson

We consider large non-Hermitian $N\times N$ matrices with an additive independent, identically distributed (i.i.d.) noise for each matrix elements. We show that already a small noise of variance $1/N$ completely thermalises the bulk…

Probability · Mathematics 2024-01-12 Giorgio Cipolloni , László Erdős , Joscha Henheik , Dominik Schröder

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

In this text, based on elementary computations, we provide a perturbative expansion of the coordinates of the eigenvectors of a Hermitian matrix of large size perturbed by a random matrix with small operator norm whose entries in the…

Probability · Mathematics 2020-03-19 Florent Benaych-Georges , Nathanaël Enriquez , Alkéos Michaïl

A remarkable extension of Rayleigh-Schroedinger perturbation method is found. Its (N+q) x (N+1) - dimensional Hamiltonians (as emerging, e.g., during quasi-exact constructions of bound states) are non-square matrices at q > 1. The role of…

Mathematical Physics · Physics 2007-05-23 Miloslav Znojil

Let $$ A=\left(\begin{array}{cc} H_1 & E^*\\ E & H_2\end{array}\right) \quad \hbox{ and } \quad \wtd A=\left(\begin{array}{cc} H_1 & O\\ O & H_2\end{array}\right)$$ be two $N$-by-$N$ Hermitian matrices with eigenvalues $\lambda_1 \ge \cdots…

Numerical Analysis · Mathematics 2025-08-12 Chi-Kwong Li , Ren-Cang Li

We present first-order perturbation analysis of a simple eigenvalue and the corresponding right and left eigenvectors of a general square matrix, not assumed to be Hermitian or normal. The eigenvalue result is well known to a broad…

Numerical Analysis · Mathematics 2019-06-04 Anne Greenbaum , Ren-cang Li , Michael L. Overton

A large i.i.d. random matrix with deterministic low-rank perturbation has been extensively studied, particularly in the aspects of the ESD (Empirical Spectral Distribution) and the outliers of eigenvalues. In this work, we investigate the…

Information Theory · Computer Science 2025-06-24 Kun Chen , Zhihua Zhang

Quantum mechanics of unitary systems is considered in quasi-Hermitian representation. In this framework the concept of perturbation is found counterintuitive, for three reasons. The first one is that in this formalism we are allowed to…

Quantum Physics · Physics 2024-05-21 Miloslav Znojil

In statistics and machine learning, people are often interested in the eigenvectors (or singular vectors) of certain matrices (e.g. covariance matrices, data matrices, etc). However, those matrices are usually perturbed by noises or…

Statistics Theory · Mathematics 2017-06-05 Jianqing Fan , Weichen Wang , Yiqiao Zhong

Many problems in physics, chemistry and other fields are perturbative in nature, i.e. differ only slightly from related problems with known solutions. Prominent among these is the eigenvalue perturbation problem, wherein one seeks the…

Mathematical Physics · Physics 2020-03-12 Maseim Kenmoe , Matteo Smerlak , Anton Zadorin

We analyze the distribution of eigenvectors for mesoscopic, mean-field perturbations of diagonal matrices in the bulk of the spectrum. Our results apply to a generalized $N\times N$ Rosenzweig-Porter model. We prove that the eigenvectors…

Probability · Mathematics 2020-11-04 Lucas Benigni

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

In this paper the perturbation theory with the frequency of transition in atom as perturbation parameter is constructed. The estimation of the reminder term of series of this perturbation theory is given. With the help of this perturbation…

Mathematical Physics · Physics 2007-05-23 Eduard Tur

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 consider a diffusive matrix process $(X_t)_{t\ge 0}$ defined as $X_t:=A+H_t$ where $A$ is a given deterministic Hermitian matrix and $(H_t)_{t\ge 0}$ is a Hermitian Brownian motion. The matrix $A$ is the "external source" that one would…

Probability · Mathematics 2015-01-21 Romain Allez , Joël Bun , Jean-Philippe Bouchaud
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