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arXiv · 2610.10494

Rectangular matrix multiplication from shared-leg entropy

Przemyslaw Uznanski
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Abstract

In this note, we extend the analysis underlying a recent matrix-multiplication result by OpenAI to rectangular products and prove that $ω(1,k,1)\le 2$ for $0\le k\le \frac{1}{2}$ and $ω(1,k,1)\le 1+k+\frac{1}{4k}$ for $k\ge \frac{1}{2}$. In particular, $ω(1,\frac{1}{2},1)=2$ and the dual exponent satisfies $α\ge \frac{1}{2}$. We use the shared-leg entropy inequality and polynomial-multiplication degenerations from that work, retaining two-leg symmetry and the orientation of each sector. Logarithmic averaging produces homogeneous auxiliary profiles. Their powered versions have a common asymptotic slope, and bounding their intercepts gives the spectral constraint $b\le 4a(1-a)$. This yields the rectangular curve by tensor-spectrum duality. As an application, Zwick's algorithm for all-pairs shortest paths in directed unweighted graphs runs in $O(n^{2.5})$ time. Combining the rectangular bound with the $(\min,+)$-product improvement of Alman and Vassilevska Williams further gives $O(n^{2.4999})$ running time.

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Przemyslaw Uznanski. 2026-10-07. Rectangular matrix multiplication from shared-leg entropy. https://arxiv.org/abs/2610.10494

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