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| Main Author: | |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.17764 |
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| _version_ | 1866908300882214912 |
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| author | San-José, Rodrigo |
| author_facet | San-José, Rodrigo |
| contents | We generalize the Brouwer-Zimmermann algorithm, which is the most efficient general algorithm for computing the minimum distance of a random linear code, to the case of generalized Hamming weights. We also adapt this algorithm to compute the relative generalized Hamming weights of a nested pair of linear codes. In the package GHWs we provide an implementation of this algorithm in Sage, as well as several other utilities for working with generalized Hamming weights. With this implementation, we show that the proposed algorithm is faster than the naive approach of computing the generalized Hamming weights using the definition. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_17764 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An algorithm for computing generalized Hamming weights and the Sage package GHWs San-José, Rodrigo Information Theory We generalize the Brouwer-Zimmermann algorithm, which is the most efficient general algorithm for computing the minimum distance of a random linear code, to the case of generalized Hamming weights. We also adapt this algorithm to compute the relative generalized Hamming weights of a nested pair of linear codes. In the package GHWs we provide an implementation of this algorithm in Sage, as well as several other utilities for working with generalized Hamming weights. With this implementation, we show that the proposed algorithm is faster than the naive approach of computing the generalized Hamming weights using the definition. |
| title | An algorithm for computing generalized Hamming weights and the Sage package GHWs |
| topic | Information Theory |
| url | https://arxiv.org/abs/2503.17764 |