General Tridiagonal Random Matrix Models, Limiting Distributions and Fluctuations
Ionel Popescu
Abstract
In this paper we discuss general tridiagonal matrix models which are natural extensions of the ones given by Dumitriu and Edelman. We prove here the convergence of the distribution of the eigenvalues and compute the limiting distributions in some particular cases. We also discuss the limit of fluctuations, which, in a general context, turn out to be Gaussian. For the case of several random matrices, we prove the convergence of the joint moments and the convergence of the fluctuations to a Gaussian family.
Create a lesson
Related papers
Distribution-constrained optimal multiple stopping: the Root-type solution
Shuoqing Deng, Daxin Huang
Universality and sharp thresholds for ellipsoid fitting
Frederic Koehler, Youngtak Sohn
Local Laws and Edge Universality for Noncentral Sample Covariance Matrices
Can Hu, Jiang Hu, Zhidong Bai
Well-posedness and regularity of stochastic heat equations on moving domains
Chongyang Ren, Tusheng Zhang
Traveling Waves in Equity Markets with Rank-Based Entry and Exit
Graeme Baker, Caroline Smyth
An approximate zero bias transformation for random sums: Applications to sampling with outliers, auto insurance, and generative AI
Wasamon Jantai, Nathakhun Wiroonsri