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Finding short lattice vectors within mordell's inequality
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Annual ACM Symposium on Theory of Computing archive
Proceedings of the 40th annual ACM symposium on Theory of computing table of contents
Victoria, British Columbia, Canada
SESSION: 5A table of contents
Pages 207-216  
Year of Publication: 2008
ISBN:978-1-60558-047-0
Authors
Nicolas Gama  Ecole normale superieure, INRIA, CNRS, Paris, France
Phong Q. Nguyen  Ecole normale superieure, CNRS, INRIA, Paris, France
Sponsors
ACM: Association for Computing Machinery
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
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ABSTRACT

The celebrated Lenstra-Lenstra-Lovász lattice basis reduction algorithm (LLL) can naturally be viewed as an algorithmic version of Hermite's inequality on Hermite's constant. We present a polynomial-time blockwise reduction algorithm based on duality which can similarly be viewed as an algorithmic version of Mordell's inequality on Hermite's constant. This achieves a better and more natural approximation factor for the shortest vector problem than Schnorr's algorithm and its transference variant by Gama, Howgrave-Graham, Koy and Nguyen. Furthermore, we show that this approximation factor is essentially tight in the worst case.


REFERENCES

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Collaborative Colleagues:
Nicolas Gama: colleagues
Phong Q. Nguyen: colleagues