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Probabilistic analysis of block Wiedemann for leading invariant factors.

Authors :
Harrison, Gavin
Johnson, Jeremy
Saunders, B. David
Source :
Journal of Symbolic Computation. Jan2022, Vol. 108, p98-116. 19p.
Publication Year :
2022

Abstract

We determine the probability, structure dependent, that the block Wiedemann algorithm correctly computes leading invariant factors. This leads to a tight lower bound for the probability, structure independent. We show, using block size slightly larger than r , that the leading r invariant factors are computed correctly with high probability over any field. Moreover, an algorithm is provided to compute the probability bound for a given matrix size and thus to select the block size needed to obtain the desired probability. The worst case probability bound is improved, post hoc, by incorporating the partial information about the invariant factors. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07477171
Volume :
108
Database :
Academic Search Index
Journal :
Journal of Symbolic Computation
Publication Type :
Academic Journal
Accession number :
151634379
Full Text :
https://doi.org/10.1016/j.jsc.2021.06.005