On the concentration of eigenvalues of random symmetric matrices
Israel Journal of MathematicsPublished 1 December 2002
Noga Alon, Michael Krivelevich, Van H. Vu
Citations140
SJR quartileQ1
SJR score0.95
SNIP1.11
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
It is shown that for every 1≤s≤n, the probability that thes-th largest eigenvalue of a random symmetricn-by-n matrix with independent random entries of absolute value at most 1 deviates from its median by more thant is at most 4e − t 232 s2. The main ingredient in the proof is Talagrand's Inequality for concentration of measure in product spaces.
Keywords
Mathematics
Medical Entomology and ZoologyThe Probabilistic Method
4,356 Citations1991Joel Spencer
A particular set of problems - all dealing with “good” colorings of an underlying set of points relative to a given family of sets - is explored.
Communications in Mathematical PhysicsLevel-spacing distributions and the Airy kernel
1,900 Citations1994Craig A. Tracy, Harold Widom
Annals of MathematicsOn the Distribution of the Roots of Certain Symmetric Matrices
1,458 Citations1958E. P. Wigner
The distribution law obtained before' for a very special set of matrices is valid for much more general sets of real symmetric matrices of very high dimensionality.
Publications mathématiques de l IHÉSConcentration of measure and isoperimetric inequalities in product spaces
862 Citations1995Michel Talagrand
Communications in Mathematical PhysicsOn orthogonal and symplectic matrix ensembles
763 Citations1996Craig A. Tracy, Harold Widom
Characteristic Vectors of Bordered Matrices with Infinite Dimensions II
686 Citations1993E. P. Wigner
COMBINATORICAThe eigenvalues of random symmetric matrices
673 Citations1981Zoltán Füredi, János Komlós
It is shown that with probability 1-o(1)all eigenvalues belong to the above intervalI if μ=0, while in case μ>0 only the largest eigenvalueλ1 is outsideI, and λ1 asymptotically has a normal distribution with expectation (n−1)μ+v+(σ2/μ) and variance 2σ2 (bounded variance!).
Electronic Communications in ProbabilityConcentration of the Spectral Measure for Large Matrices
244 Citations2000Alice Guionnet, Ofer Zeitouni
It is derived that concentration inequalities for functions of the empirical measure of eigenvalues for large, random, self adjoint matrices, with not necessarily Gaussian entries, are derived.
Communications in Mathematical PhysicsUniversality at the Edge of the Spectrum¶in Wigner Random Matrices
243 Citations1999Alexander Soshnikov
Journal of Combinatorial OptimizationApproximating the Independence Number and the Chromatic Number in Expected Polynomial Time
45 Citations2002Michael Krivelevich, Van H. Vu
An approximation algorithm is presented for the independence number of graphs on n vertices, whose approximation ratio is O((np)1/2/log n) and whose expected running time over the probability space G(n, p) is polynomial.
Lecture notes in computer scienceApproximating the Independence Number and the Chromatic Number in Expected Polynomial Time
16 Citations2000Michael Krivelevich, H. Van Vu
