Izzy Friedlander isobel.s.friedlander@durham.ac.uk
PGR Student Doctor of Philosophy
The MacWilliams Identity for the Skew Rank Metric
Friedlander, I; Bouganis, A; Gadouleau, M
Authors
Professor Athanasios Bouganis athanasios.bouganis@durham.ac.uk
Professor
Dr Maximilien Gadouleau m.r.gadouleau@durham.ac.uk
Associate Professor
Abstract
The weight distribution of an error correcting code is a crucial statistic in determining its performance. One key tool for relating the weight of a code to that of it's dual is the MacWilliams Identity, first developed for the Hamming metric. This identity has two forms: one is a functional transformation of the weight enumerators, while the other is a direct relation of the weight distributions via (generalised) Krawtchouk polynomials. The functional transformation form can in particular be used to derive important moment identities for the weight distribution of codes. In this paper, we focus on codes in the skew rank metric. In these codes, the codewords are skew-symmetric matrices, and the distance between two matrices is the skew rank metric, which is half the rank of their difference. This paper develops a q-analog MacWilliams Identity in the form of a functional transformation for codes based on skew-symmetric matrices under their associated skew rank metric. The method introduces a skew-q
algebra and uses generalised Krawtchouk polynomials. Based on this new MacWilliams Identity, we then derive several moments of the skew rank distribution for these codes.
Citation
Friedlander, I., Bouganis, A., & Gadouleau, M. (online). The MacWilliams Identity for the Skew Rank Metric. Advances in Mathematics of Communications, https://doi.org/10.3934/amc.2023045
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 9, 2023 |
Publication Date | 2023 |
Deposit Date | Nov 2, 2022 |
Publicly Available Date | Nov 7, 2023 |
Journal | Advances in Mathematics of Communications |
Print ISSN | 1930-5346 |
Electronic ISSN | 1930-5338 |
Publisher | American Institute of Mathematical Sciences (AIMS) |
Peer Reviewed | Peer Reviewed |
DOI | https://doi.org/10.3934/amc.2023045 |
Public URL | https://durham-repository.worktribe.com/output/1186777 |
Related Public URLs | https://arxiv.org/abs/2210.16153 |
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Copyright Statement
This article has been published in a revised form in Advances in Mathematics of Communications, 10.3934/amc.2023045. This version is free to download for private research and study only. Not for redistribution, re-sale or use in derivative works.
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