Abstract : In 1982, Arjen Lenstra, Hendrik Lenstra Jr. and László Lovász introduced an efficiently computable notion of reduction of basis of a Euclidean lattice that is now commonly referred to as LLL-reduction. The precise definition involves the R-factor of the QR factorisation of the basis matrix. A natural mean of speeding up the LLL reduction algorithm is to use a (floating-point) approximation to the R-factor. In the present article, we investigate the accuracy of the factor R of the QR factorisation of an LLL-reduced basis. Our main contribution is the first fully rigorous perturbation analysis of the R-factor of LLL-reduced matrices under column-wise perturbations. Our results should be very useful to devise LLL-type algorithms relying on floating-point approximations.
https://hal-ens-lyon.archives-ouvertes.fr/ensl-00529425
Contributor : Gilles Villard
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Submitted on : Thursday, April 7, 2011 - 4:28:46 PM
Last modification on : Thursday, February 7, 2019 - 4:59:27 PM
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Xiao-Wen Chang, Damien Stehlé, Gilles Villard. Perturbation Analysis of the QR Factor R in the Context of LLL Lattice Basis Reduction. Mathematics of Computation, American Mathematical Society, 2012, 81 (279), pp.1487-1511. ⟨ensl-00529425v2⟩
