2021
DOI: 10.37236/9617
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Zero-Sum Squares in Bounded Discrepancy $\{-1,1\}$-Matrices

Abstract: For $n\geqslant 5$, we prove that every $n\times n$ matrix $\mathcal{M}=(a_{i,j})$ with entries in $\{-1,1\}$ and absolute discrepancy $\lvert\mathrm{disc}(\mathcal{M})\rvert=\lvert\sum a_{i,j}\rvert\leqslant n$ contains a zero-sum square except for the split matrices (up to symmetries). Here, a square is a $2\times 2$ sub-matrix of $\mathcal{M}$ with entries $a_{i,j}, a_{i+s,s}, a_{i,j+s}, a_{i+s,j+s}$ for some $s\geqslant 1$, and a split matrix is a matrix with all entries above the diagonal equal to $-1$ an… Show more

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Cited by 1 publication
(6 citation statements)
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“…This was confirmed by Arévalo, Montejano and Roldán-Pensado in [1]. In fact, they proved that, except when n 4, every n×n non-split {−1, 1}-matrix M with | disc(M )| n has a zero-sum square.…”
Section: Introductionmentioning
confidence: 72%
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“…This was confirmed by Arévalo, Montejano and Roldán-Pensado in [1]. In fact, they proved that, except when n 4, every n×n non-split {−1, 1}-matrix M with | disc(M )| n has a zero-sum square.…”
Section: Introductionmentioning
confidence: 72%
“…The final lemma we will use to prove Theorem 2 is a variation on Claim 11 from [1]. The main difference between Lemma 5 and the result used by Arévalo, Montejano and Roldán-Pensado is that we will always find a square submatrix, which simplifies the proof of Theorem 2.…”
Section: Lemma 3 ([1]mentioning
confidence: 97%
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