The Maximum Permanent of a Stochastic Matrix of Bounded Rank

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Contributed by Yair Lavi ↗

Version 1 / Nov 12, 2026/ arXiv: 2609.27911 / CC BY 4.0

Abstract

Let AA be a stochastic n×nn\times n matrix with rank⁡A≤k\operatorname{rank}A\leq k, where 1≤k≤n1\leq k\leq n. Write n=qk+sn=qk+s, where 0≤s<k0\leq s<k. The author conjectured in 2018 that per⁡A≤(q!/qq)k−s((q+1)!/(q+1)q+1)s\operatorname{per}A\leq (q!/q^q)^{k-s}((q+1)!/(q+1)^{q+1})^s, with equality if and only if A=P(Jq⊕(k−s)⊕Jq+1⊕s)QA=P(J_q^{\oplus(k-s)}\oplus J_{q+1}^{\oplus s})Q, where P,QP,Q are permutation matrices and JtJ_t is the t×tt\times t matrix with every entry 1/t1/t. We prove this conjecture in full.

Tools used

OpenAI
GPT-5.6-sol

References

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Version history

  1. v1 · 14 pagesSubmitted by Yair LaviInitial depositCurrentNov 11, 2026