Rankin’s Constant and Blockwise Lattice Reduction

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4117)


Lattice reduction is a hard problem of interest to both public-key cryptography and cryptanalysis. Despite its importance, extremely few algorithms are known. The best algorithm known in high dimension is due to Schnorr, proposed in 1987 as a block generalization of the famous LLL algorithm. This paper deals with Schnorr’s algorithm and potential improvements. We prove that Schnorr’s algorithm outputs better bases than what was previously known: namely, we decrease all former bounds on Schnorr’s approximation factors to their (ln 2)-th power. On the other hand, we also show that the output quality may have intrinsic limitations, even if an improved reduction strategy was used for each block, thereby strengthening recent results by Ajtai. This is done by making a connection between Schnorr’s algorithm and a mathematical constant introduced by Rankin more than 50 years ago as a generalization of Hermite’s constant. Rankin’s constant leads us to introduce the so-called smallest volume problem, a new lattice problem which generalizes the shortest vector problem, and which has applications to blockwise lattice reduction generalizing LLL and Schnorr’s algorithm, possibly improving their output quality. Schnorr’s algorithm is actually based on an approximation algorithm for the smallest volume problem in low dimension. We obtain a slight improvement over Schnorr’s algorithm by presenting a cheaper approximation algorithm for the smallest volume problem, which we call transference reduction.


Exhaustive Search Approximation Factor Output Quality Lattice Reduction Short Vector 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  1. 1.École normale supérieureParisFrance
  2. 2.NTRU CryptosystemsBurlingtonUSA
  3. 3.Deutsche Bank AGFrankfurt am MainGermany
  4. 4.CNRS/École normale supérieureParisFrance

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