Derandomizing Matrix Concentration Inequalities from Free Probability
Data Structures and Algorithms
2026-05-01 v2 Discrete Mathematics
Combinatorics
Probability
Abstract
Recently, sharp matrix concentration inequalities~\cite{BBvH23,BvH24} were developed using the theory of free probability. In this work, we design polynomial time deterministic algorithms to construct outcomes that satisfy the guarantees of these inequalities. As direct consequences, we obtain polynomial time deterministic algorithms for the matrix Spencer problem~\cite{BJM23} and for constructing near-Ramanujan graphs. Our proofs show that the concepts and techniques in free probability are useful not only for mathematical analyses but also for efficient computations.
Cite
@article{arxiv.2601.08111,
title = {Derandomizing Matrix Concentration Inequalities from Free Probability},
author = {Robert Wang and Lap Chi Lau and Hong Zhou},
journal= {arXiv preprint arXiv:2601.08111},
year = {2026}
}
Comments
105 pages with minor updates