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arXiv:2511.14653math.CO

Asymptotically optimal approximate Hadamard matrices

Boris Alexeev, John Jasper, Dustin G. Mixon

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Abstract

An approximate Hadamard matrix is a well-conditioned square matrix with all entries in $\{\pm1\}$. We measure the quality of a matrix by its condition number, i.e., the ratio of its largest and smallest singular values. We prove that for any fixed positive $α<17/92$, every sufficiently large dimension admits an approximate Hadamard matrix with condition number at most $1+n^{-α}$. In particular, the smallest possible condition number tends to $1$ as $n\to\infty$. Conversely, there exists an absolute constant $c>0$ such that for every sufficiently large $n\not\equiv0\pmod4$, every $n\times n$ matrix with entries in $\{\pm1\}$ has condition number at least $1+c(\log n)/n$. Along the way, we resolve a problem of Jaming and Matolcsi concerning flat orthogonal matrices, and we conclude by describing several explicit infinite families of approximate Hadamard matrices.

arXiv comments
See the ancillary files for best known matrices and Lean code
Journal reference
DOI
Subjects
math.COCombinatorics math.FAFunctional Analysis

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Nov 2025 to Nov 2025. Found in 1 HN submission from Nov 2025 to Nov 2025. Open submission discussions.

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    • In case anyone is curious, there is a discussion of AI in Section 5 (page 8 of the PDF). This direct link might work: https://arxiv.org/pdf/2511.14653#page=8

      areyousureView on HNParent context

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