2021
DOI: 10.1016/j.jcta.2020.105395
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Small weight codewords of projective geometric codes

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Cited by 6 publications
(7 citation statements)
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“…In general, finding the minimum distance of a linear code and classifying its nonzero codewords of minimum weight is not an easy task. Even for linear codes from geometric constructions, it is often highly non-trivial to find sharp bounds or a classification of the smallest weight words, see for example [1,3,17,26,35].…”
Section: Coding Theory and Moderate-density Parity-check Codesmentioning
confidence: 99%
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“…In general, finding the minimum distance of a linear code and classifying its nonzero codewords of minimum weight is not an easy task. Even for linear codes from geometric constructions, it is often highly non-trivial to find sharp bounds or a classification of the smallest weight words, see for example [1,3,17,26,35].…”
Section: Coding Theory and Moderate-density Parity-check Codesmentioning
confidence: 99%
“…The family of MDPC codes that we are considering is built upon a parity-check matrix as in (1). In such a matrix the number of columns is twice the number of rows and this coincides with the setting originally studied in [24].…”
Section: Remark 49mentioning
confidence: 99%
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“…Note that if q ∈ {16, 27} and n = 3, then Theorem 1.5 follows from the (j, k) = (0, 2) case of Result 1.1; all other values of q and n 3 not satisfying (1) provide non-positive upper bounds on the weights wt(c) and hence make Theorem 1.5 trivially true. This means that the explicit assumptions on q isn't necessary for the theorem to stay true; we however keep the assumptions (1) to emphasize that we may assume q to be big.…”
Section: Introductionmentioning
confidence: 99%