An upper bound on the smallest singular value of dense random combinatorial matrices
Let M be an n × n random matrix with entries in { 0 , 1 } , where each row is independently and uniformly sampled from the set of all vectors in { 0 , 1 } n containing exactly d ones, with d = p n for some fixed constant p ∈ ( 0 , 1 / 2 ] . A recent result of Tran states that the smallest singular value s n ( M ) is bounded below by c p n − 1 / 2 with high probability. In this note, we establish a complementary upper bound for s n ( M ) , proving that ∀ ε > 0 P ( s n ( M ) ≤ d ε 2 n ) ≥ 1 − C p ( ε + 1 d ) , where C p is a positive constant depending only on p . This result confirms that the least singular value s n ( M ) of dense random combinatorial matrices is typically of the order n − 1 / 2 .
Authors
- Dongbin Li (ORCID: https://orcid.org/0009-0003-3669-8869)
- Alexander E. Litvak
- Tingzhou Yu (ORCID: https://orcid.org/0009-0005-0414-7522)
Institutions
- University of Alberta (CA)
Publication Details
- Journal
- Journal of Complexity
- Published
- 2026-03-03
- DOI
- https://doi.org/10.1016/j.jco.2026.102031
- Primary Topic
- Limits and Structures in Graph Theory
- Type
- article
- Field-Weighted Citation Impact
- 0.00