The worst-case behavior of schnorr's algorithm approximating the shortest nonzero vector in a lattice

• Authors: Miklos Ajtai
• Venue: Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
• Year: 2003

Schnorr's algorithm for finding an approximation for the shortest nonzero vector in an n dimensional lattice depends on a parameter k. He proved that for a fixed k ≤ n his algorithm (block 2k-reduction) provides a lattice vector whose length is greater than the length of a shortest nonzero vector in the lattice by at most a factor of (4k2) n/k. (The time required by the algorithm depends on k.) We show that if k=o(n), this bound on the performance of Schnorr's algorithm cannot be improved (apart from a constant factor in the exponent), namely there is a lattice and a basis so that if they are given as an input to the algorithm then the resulting approximating factor of the output is at least k ε n/k. (For larger integers k if Schnorr's algorithm runs in polynomial time then we have already a polynomial time algorithm for finding the shortest nonzero vector.) We also solve an open problem formulated by Schnorr about the the Korkine-Zolotareff lattice constants αk. We show that his upper bound αk ≤ k1 + ln k is the best possible apart from a constant factor in the exponent. We prove a similar result about his upper bound βk≤ 4k2, where βk is another lattice constant with an important role in Schnorr's analysis of his algorithm.