A probabilistic construction of maximum -scattered subspaces
Alessandro Giannoni, Alessandro Neri
Source abstract
Let and . We prove that, for every prime power , a maximum -scattered -subspace of exists whenever and In particular, for fixed and minimum distance , -linear MRD codes of length exist for every and every sufficiently large such that divides , with a bound on depending only on and . We take the -span of the columns of a random matrix over the algebra , for a suitable . Such a subspace is maximum -scattered if and only if the kernel of contains no nonzero vector whose expansion with respect to an -basis of has rank weight at most . When , is a field, and a first-moment argument, counting these vectors up to multiplication by , shows that with positive probability the kernel contains none of them if . When , is a product of fields, and vectors vanishing in some factors lie in the kernel with larger probability. We control them by proving that, for an -dimensional -subspace of , the elements of vanishing outside given factors, , form an -space of dimension at most , with equality only if is linear over a subfield of larger than . Taking gives the bound on . Finally, if , then for every satisfying the above inequality there is an -scattered -subspace of of dimension , without a divisibility condition on .
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