Abstract

A generalized hypercube graph $\Q_n(S)$ has $\F_{2}^{n}=\{0,1\}^n$ as the vertex set and two vertices being adjacent whenever their mutual Hamming distance belongs to $S$, where $n \ge 1$ and $S\subseteq \{1,2,\ldots, n\}$. The graph $\Q_n(\{1\})$ is the $n$-cube, usually denoted by $\Q_n$. We study graph boolean products $G_1 = \Q_n(S)\times \Q_1, G_2 = \Q_{n}(S)\wedge \Q_1$, $G_3 = \Q_{n}(S)[\Q_1]$ and show that binary codes from neighborhood designs of $G_1, G_2$ and $G_3$ are self-orthogonal for all choices of $n$ and $S$. More over, we show that the class of codes $C_1$ are self-dual. Further we find subgroups of the automorphism group of these graphs and use these subgroups to obtain PD-sets for permutation decoding. As an example we find a full error-correcting PD set for the binary $[32, 16, 8]$ extremal self-dual code.

Highlights

  • The generalized hypercube graphs Qn(S) were introduced in Berrachedi and Mollard [1], where the authors mainly investigated the graph embeddings especially when the underlying graph is a hypercube

  • We study graph boolean products G1 = Qn(S) × Q1, G2 = Qn(S) ∧ Q1, G3 = Qn(S)[Q1] and show that binary codes from neighborhood designs of G1, G2 and G3 are self-orthogonal for all choices of n and S

  • In this paper we study generalized hypercube graphs and binary codes from the neighborhood designs of their boolean products

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Summary

Introduction

The generalized hypercube graphs Qn(S) were introduced in Berrachedi and Mollard [1], where the authors mainly investigated the graph embeddings especially when the underlying graph is a hypercube Their connections to (0, 2)-graphs were studied in Laborde and Madani [6]. Binary codes from the row span of an adjacency matrix for the n-cube were first examined in Key and Seneviratne [5] and the codes in the case of n even were found to be self-dual with minimum weight n. In this paper we study generalized hypercube graphs and binary codes from the neighborhood designs of their boolean products.

Background and terminology
Graphs
Permutation decoding
Conclusion
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