On the largest and the smallest singular value of sparse rectangular random matrices
Open Access
- 1 January 2023
- journal article
- research article
- Published by Institute of Mathematical Statistics in Electronic Journal of Probability
- Vol. 28 (none) , 1-18
Abstract
We derive estimates for the largest and smallest singular values of sparse rectangular N×n random matrices, assuming limN,n→∞n N=y∈(0,1). We consider a model with sparsity parameter pN such that NpN∼logαN for some α>1, and assume that the moments of the matrix elements satisfy the condition E|Xjk|4+δ≤C<∞. We assume also that the entries of matrices we consider are truncated at the level (NpN)1 2−ϰ with ϰ:=δ 2(4+δ).Keywords
All Related Versions
This publication has 17 references indexed in Scilit:
- The sparse circular law under minimal assumptionsGeometric and Functional Analysis, 2019
- A necessary and sufficient condition for edge universality at the largest singular values of covariance matricesThe Annals of Applied Probability, 2018
- Eigenvector statistics of sparse random matricesElectronic Journal of Probability, 2017
- The smallest singular value of random rectangular matrices with no moment assumptions on entriesIsrael Journal of Mathematics, 2016
- Spectral statistics of Erdős–Rényi graphs I: Local semicircle lawThe Annals of Probability, 2013
- The circular law for random matricesThe Annals of Probability, 2010
- Smallest singular value of a random rectangular matrixCommunications on Pure and Applied Mathematics, 2009
- The Littlewood–Offord problem and invertibility of random matricesAdvances in Mathematics, 2008
- Smallest singular value of random matrices and geometry of random polytopesAdvances in Mathematics, 2005
- The Expected Norm of Random MatricesCombinatorics, Probability and Computing, 2000