Perturbation Analysis of the QR factor R in the context of LLL lattice basis reduction
Xiao-Wen Chang, Damien Stehlé, Gilles Villard · Mathematics of Computation · 2012
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 factorization of the basis matrix. In order to circumvent the use of rational/exact arithmetic with large bit-sizes, it is tempting to consider using floating-point arithmetic with small precision to compute 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 columnwise perturbations. Our results are very useful to devise LLL-type algorithms relying on floating-point approximations.