Improved Upper Bound for the Size of a Trifferent Code

IF 1 2区 数学 Q1 MATHEMATICS Combinatorica Pub Date : 2024-12-18 DOI:10.1007/s00493-024-00130-2
Siddharth Bhandari, Abhishek Khetan
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Abstract

A subset \(\mathcal {C}\subseteq \{0,1,2\}^n\) is said to be a trifferent code (of block length n) if for every three distinct codewords \(x,y, z \in \mathcal {C}\), there is a coordinate \(i\in \{1,2,\ldots ,n\}\) where they all differ, that is, \(\{x(i),y(i),z(i)\}\) is same as \(\{0,1,2\}\). Let T(n) denote the size of the largest trifferent code of block length n. Understanding the asymptotic behavior of T(n) is closely related to determining the zero-error capacity of the (3/2)-channel defined by Elias (IEEE Trans Inform Theory 34(5):1070–1074, 1988), and is a long-standing open problem in the area. Elias had shown that \(T(n)\le 2\times (3/2)^n\) and prior to our work the best upper bound was \(T(n)\le 0.6937 \times (3/2)^n\) due to Kurz (Example Counterexample 5:100139, 2024). We improve this bound to \(T(n)\le c \times n^{-2/5}\times (3/2)^n\) where c is an absolute constant.

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如果对于每三个不同的编码词(x,y、z)中,有一个坐标(i/in \{1,2,\ldots ,n/})它们都不同,也就是说,({x(i),y(i),z(i))与({0,1,2})相同。了解 T(n) 的渐近行为与确定 Elias 定义的 (3/2)-channel 的零误码容量密切相关(IEEE Trans Inform Theory 34(5):1070-1074, 1988),这也是该领域一个长期未决的问题。埃利亚斯证明了(T(n))是(3/2)^n()的2倍,而在我们的研究之前,库尔兹(Example Counterexample 5:100139, 2024)提出的最佳上界是(T(n))是(3/2)^n()的0.6937倍。我们将这个界限改进为 \(T(n)\le c \times n^{-2/5}\times (3/2)^n\) 其中 c 是一个绝对常数。
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来源期刊
Combinatorica
Combinatorica 数学-数学
CiteScore
1.90
自引率
0.00%
发文量
45
审稿时长
>12 weeks
期刊介绍: COMBINATORICA publishes research papers in English in a variety of areas of combinatorics and the theory of computing, with particular emphasis on general techniques and unifying principles. Typical but not exclusive topics covered by COMBINATORICA are - Combinatorial structures (graphs, hypergraphs, matroids, designs, permutation groups). - Combinatorial optimization. - Combinatorial aspects of geometry and number theory. - Algorithms in combinatorics and related fields. - Computational complexity theory. - Randomization and explicit construction in combinatorics and algorithms.
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