Semidefinite bounds for mixed binary/ternary codes

TL;DR

This paper develops semidefinite programming bounds for mixed binary/ternary codes, providing 135 new upper bounds on code sizes with specified minimum distances by exploiting symmetry and representation theory.

Contribution

It introduces a novel semidefinite programming approach for mixed binary/ternary codes and reduces computational complexity through symmetry exploitation, resulting in new upper bounds.

Findings

135 new upper bounds for code sizes

Semidefinite bounds improve previous estimates

Method applicable to mixed binary/ternary codes

Abstract

For nonnegative integers $n_2, n_3$ and $d$, let $N(n_2,n_3,d)$ denote the maximum cardinality of a code of length $n_2+n_3$, with $n_2$ binary coordinates and $n_3$ ternary coordinates (in this order) and with minimum distance at least $d$. For a nonnegative integer $k$, let $\mathcal{C}_k$ denote the collection of codes of cardinality at most $k$. For $D \in \mathcal{C}_k$, define $S(D) := \{C \in \mathcal{C}_k \mid D \subseteq C, |D| +2|C\setminus D| \leq k\}$. Then $N(n_2,n_3,d)$ is upper bounded by the maximum value of $\sum_{v \in [2]^{n_2}[3]^{n_3}}x(\{v\})$, where $x$ is a function $\mathcal{C}_k \rightarrow \mathbb{R}$ such that $x(\emptyset) = 1$ and $x(C) = 0$ if $C$ has minimum distance less than $d$, and such that the $S(D)\times S(D)$ matrix $(x(C\cup C'))_{C,C' \in S(D)}$ is positive semidefinite for each $D \in \mathcal{C}_k$. By exploiting symmetry, the semidefinite programming problem for the case $k=3$ is reduced using representation theory. It yields $135$ new upper bounds that are provided in tables