Spectral radius of random matrices with independent entries
Johannes Alt, László Erdős, Torben Krüger
Abstract
We consider random $n\times n$ matrices $X$ with independent and centered entries and a general variance profile. We show that the spectral radius of $X$ converges with very high probability to the square root of the spectral radius of the variance matrix of $X$ when $n$ tends to infinity. We also establish the optimal rate of convergence, that is a new result even for general i.i.d. matrices beyond the explicitly solvable Gaussian cases. The main ingredient is the proof of the local inhomogeneous circular law [arXiv:1612.07776] at the spectral edge.
Topics & Concepts
MathematicsSpectral radiusCircular lawRandom matrixGaussianRADIUSMatrix (chemical analysis)InfinityCombinatoricsVariance (accounting)Square rootConvergence (economics)Mathematical analysisRandom variableConvergence of random variablesGeometryPhysicsStatisticsEigenvalues and eigenvectorsQuantum mechanicsSum of normally distributed random variablesMaterials scienceComposite materialBusinessComputer securityAccountingEconomicsComputer scienceEconomic growthRandom Matrices and ApplicationsStochastic processes and statistical mechanicsPoint processes and geometric inequalities