9,553 research outputs found
Minimal Polynomial Algorithms for Finite Sequences
We show that a straightforward rewrite of a known minimal polynomial
algorithm yields a simpler version of a recent algorithm of A. Salagean.Comment: Section 2 added, remarks and references expanded. To appear in IEEE
Transactions on Information Theory
Interactive certificate for the verification of Wiedemann's Krylov sequence: application to the certification of the determinant, the minimal and the characteristic polynomials of sparse matrices
Certificates to a linear algebra computation are additional data structures
for each output, which can be used by a-possibly randomized- verification
algorithm that proves the correctness of each output. Wiede-mann's algorithm
projects the Krylov sequence obtained by repeatedly multiplying a vector by a
matrix to obtain a linearly recurrent sequence. The minimal polynomial of this
sequence divides the minimal polynomial of the matrix. For instance, if the
input matrix is sparse with n 1+o(1) non-zero entries, the
computation of the sequence is quadratic in the dimension of the matrix while
the computation of the minimal polynomial is n 1+o(1), once that projected
Krylov sequence is obtained. In this paper we give algorithms that compute
certificates for the Krylov sequence of sparse or structured
matrices over an abstract field, whose Monte Carlo verification complexity can
be made essentially linear. As an application this gives certificates for the
determinant, the minimal and characteristic polynomials of sparse or structured
matrices at the same cost
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