Nguyen's singularity conjecture for random matrices with fixed row sums
Nguyen's singularity conjecture for random matrices with fixed row sums
Let be a random matrix whose independent rows are chosen uniformly from the vectors in having sum exactly . Nguyen's conjecture.
This model is a dependent-entry analogue of random adjacency matrices of regular directed graphs and serves as a test bed for inverse Littlewood–Offord questions. The source states that the paper resolves Nguyen’s conjecture.
Sources & referencesView supporting material
Primary source
Vishesh Jain, Ashwin Sah and Mehtaab Sawhney, “Sharp invertibility of random Bernoulli matrices”, arXiv:2010.06553 (2021).
Additional references
2 papers in this index state this conjecture (2020). The statement above is taken from the most recent of them; the others are arXiv:2007.06318.
Progress summary
The conjecture remains open: known work shows singular matrices are very rare, but not the precise exponential rate predicted.
Nguyen conjectured that for the fixed-row-sum random matrix model, the singularity probability is asymptotic to . The conjecture was posed in Nguyen’s work after identifying equal rows as the apparent dominant source of singularity.
Known results
- Nguyen proved, for even , that for every .
- Equal rows give the lower bound .
- Subsequent work proved exponential upper bounds, including , but not the conjectured asymptotic.
Current status (as of August 2026): The conjectured asymptotic remains unproved; only polynomial and exponential-scale nonsingularity estimates are established.
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