2014
DOI: 10.37236/3534
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Constant Rank-Distance Sets of Hermitian Matrices and Partial Spreads in Hermitian Polar Spaces

Abstract: In this paper we investigate partial spreads of H(2n−1, q 2 ) through the related notion of partial spread sets of hermitian matrices, and the more general notion of constant rank-distance sets. We prove a tight upper bound on the maximum size of a linear constant rank-distance set of hermitian matrices over finite fields, and as a consequence prove the maximality of extensions of symplectic semifield spreads as partial spreads of H(2n − 1, q 2 ). We prove upper bounds for constant rank-distance sets for even … Show more

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Cited by 6 publications
(11 citation statements)
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“…A good overview of MRD-codes can be found in [36]. Similar problems for symmetric, alternating and hermitian matrices have been studied in for example [16], [38], [20], [18].…”
Section: Rank Metric Codesmentioning
confidence: 99%
“…A good overview of MRD-codes can be found in [36]. Similar problems for symmetric, alternating and hermitian matrices have been studied in for example [16], [38], [20], [18].…”
Section: Rank Metric Codesmentioning
confidence: 99%
“…We close this section by showing that the bound for additive codes in Theorem 1 can be surpassed by non-additive codes whenever n is even and d = n. This follows already from [11,Theorem 9]. Here we give a more direct construction.…”
Section: Constructionsmentioning
confidence: 72%
“…It should be noted that related, but different, rank properties of sets of Hermitian matrices have been studied in [9] and [11].…”
Section: Introductionmentioning
confidence: 99%
“…Remark 1. Note that an n-dimensional dual hyperoval is a special case of a constant-distance, constant-dimension subspace code [8], [9], or equivalently, a clique in the graph Γ n−1 , where Γ i is the graph whose vertices are the vertices of Γ, and whose edges are between vertices at distance i in Γ. Note however that not every clique of the correct size in Γ n−1 gives rise to an n-dimensional dual hyperoval.…”
Section: Proof Of Theoremmentioning
confidence: 99%