← 研踪 PaperTrailarXiv:2611.16299 · v1
Improved Lower Bounds for Mutually Orthogonal Latin Squares (MOLS) at 33 Orders
首次提交 2026-11-12 12:55
版本更新 2026-11-12 12:55
雷达观测 2026-11-13 14:16
摘要
A Latin square of order is an array over symbols , such that the same symbol does not appear twice in any row or any column. Two Latin squares of order are orthogonal if, when superimposed, they yield each of the ordered pairs of symbols exactly once. A set of two or more Latin squares are mutually orthogonal Latin squares (MOLS) if each pair of distinct squares is orthogonal. Let be the maximum size of a set of MOLS of order . For most which are not prime powers, there is a wide gap between known upper and lower bounds on . This has led to interest in constructing new larger sets of MOLS for explicit values of , to incrementally improve the lower bounds on . This paper provides MOLS that improve the lower bound on for 33 values of in the range from 22 through 494. The constructions were found by GPT-6 Astra, and use established techniques including difference matrices, quasi-difference matrices, orthogonal arrays, and projective planes. A highlight is 4 MOLS of order ; combined with pre-existing results, this establishes for all .
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v1 · 2026-11-12 12:55 · 最新观测版本
Improved Lower Bounds for Mutually Orthogonal Latin Squares (MOLS) at 33 Orders
A Latin square of order is an array over symbols , such that the same symbol does not appear twice in any row or any column. Two Latin squares of order are orthogonal if, when superimposed, they yield each of the ordered pairs of symbols exactly once. A set of two or more Latin squares are mutually orthogonal Latin squares (MOLS) if each pair of distinct squares is orthogonal. Let be the maximum size of a set of MOLS of order . For most which are not prime powers, there is a wide gap between known upper and lower bounds on . This has led to interest in constructing new larger sets of MOLS for explicit values of , to incrementally improve the lower bounds on . This paper provides MOLS that improve the lower bound on for 33 values of in the range from 22 through 494. The constructions were found by GPT-6 Astra, and use established techniques including difference matrices, quasi-difference matrices, orthogonal arrays, and projective planes. A highlight is 4 MOLS of order ; combined with pre-existing results, this establishes for all .
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