Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-27T21:58:48.707Z Has data issue: false hasContentIssue false

On the reduction of a random basis

Published online by Cambridge University Press:  22 September 2009

Ali Akhavi
Affiliation:
LIAFA, Université Denis Diderot, Case 7014, 2 place Jussieu, 75251 Paris Cedex 05, France; akhavi@liafa.jussieu.fr
Jean-François Marckert
Affiliation:
LABRI, Université Bordeaux I, 351 cours de la Libération, 33405 Talence Cedex, France; marckert@labri.fr
Alain Rouault
Affiliation:
LMV UMR 8100, Université Versailles-Saint-Quentin, 45 avenue des États-Unis, 78035 Versailles Cedex, France; Alain.Rouault@math.uvsq.fr
Get access

Abstract

For p ≤ n, let b1(n),...,bp(n) be independent random vectors in $\mathbb{R}^n$ with the same distribution invariant by rotation and without mass at the origin. Almost surely these vectors form a basis for the Euclidean lattice they generate. The topic of this paper is the property of reduction of this random basis in the sense of Lenstra-Lenstra-Lovász (LLL). If $\widehat b_{1}^{(n)},\ldots, \widehat b_p^{(n)}$ is the basis obtained from b1(n),...,bp(n) by Gram-Schmidt orthogonalization, the quality of the reduction depends upon the sequence of ratios of squared lengths of consecutive vectors $r_j^{(n)} = \Vert \widehat b^{(n)}_{n-j+1}\Vert^2 / \Vert \widehat b^{(n)}_{n-j} \Vert^2$ , j = 1,...,p - 1. We show that as n → +∡ the process $(r_j^{(n)}-1,j\geq 1)$ tends in distribution in some sense to an explicit process $({\mathcal R}_j -1,j\geq 1)$ ; some properties of the latter are provided. The probability that a random random basis is s-LLL-reduced is then showed to converge for p = n - g, and g fixed, or g = g(n) → +∞.

Type
Research Article
Copyright
© EDP Sciences, SMAI, 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abbott, J. and Mulders, T., How tight is Hadamard bound? Experiment. Math. 10 (2001) 331336. CrossRef
A. Akhavi, Analyse comparative d'algorithmes de réduction sur les réseaux aléatoires. Ph.D. thesis, Université de Caen (1999).
Akhavi, A., Random lattices, threshold phenomena and efficient reduction algorithms. Theor. Comput. Sci. 287 (2002) 359385. CrossRef
A. Akhavi, J.-F. Marckert and A. Rouault. On the reduction of a random basis, in D. Applegate, G.S. Brodal, D. Panario and R. Sedgewick Eds. Proceedings of the ninth workshop on algorithm engineering and experiments and the fourth workshop on analytic algorithmics and combinatorics. New Orleans (2007).
T.W. Anderson, An introduction to multivariate statistical analysis. Wiley Series in Probability and Statistics, Third edition. John Wiley (2003).
Chaganthy, N.R., Large deviations for joint distributions and statistical applications. Sankhya 59 (1997) 147166.
L. Chaumont and M. Yor, Exercises in probability. Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge University Press, Cambridge (2003).
Daudé, H. and Vallée, B., An upper bound on the average number of iterations of the LLL algorithm. Theor. Comput. Sci. 123 (1994) 95115. CrossRef
Dixon, J.D., How good is Hadamard's inequality for determinants? Can. Math. Bull. 27 (1984) 260264. CrossRef
Donaldson, J.L., Minkowski reduction of integral matrices. Math. Comput. 33 (1979) 201216. CrossRef
A. Edelman and N.R. Rao, Random matrix theory. Acta Numerica (2005) 1–65.
Gan, Y.H., Ling, C., and Mow, W.H., Complex Lattice Reduction Algorithm for Low-Complexity MIMO Detection. IEEE Trans. Signal Processing 57 (2009) 27012710.
Hadamard, J., Résolution d'une question relative aux déterminants. Bull. Sci. Math. 17 (1893) 240246.
R. Kannan, Algorithmic geometry of numbers, in Annual review of computer science, Vol. 2. Annual Reviews, Palo Alto, CA (1987) 231–267.
D.E. Knuth, The art of computer programming, Vol. 2. Addison-Wesley Publishing Co., Reading, Mass., second edition. Seminumerical algorithms, Addison-Wesley Series in Computer Science and Information Processing (1981).
Koy, H. and Schnorr, C.P., Segment LLL-Reduction of Lattice Bases. Lect. Notes Comput. Sci. 2146 (2001) 67. CrossRef
Lenstra Jr, H.W.., Integer programming and cryptography. Math. Intelligencer 6 (1984) 1419. CrossRef
H.W. Lenstra Jr., Flags and lattice basis reduction. In European Congress of Mathematics, Vol. I (Barcelona, 2000). Progr. Math. 201 37–51. Birkhäuser, Basel (2001).
Lenstra, A.K., Lenstra Jr, H.W.. and L. Lovász, Factoring polynomials with rational coefficients. Math. Ann. 261 (1982) 515534. CrossRef
Letac, G., Isotropy and sphericity: some characterisations of the normal distribution. Ann. Statist. 9 (1981) 408417. CrossRef
R.J. Muirhead, Aspects of multivariate statistical theory. John Wiley (1982).
Napias, H., A generalization of the LLL-algorithm over euclidean rings or orders. Journal de théorie des nombres de Bordeaux 8 (1996) 387396. CrossRef
Nguyen, P.Q. and Stern, J., The two faces of lattices in cryptology. In Cryptography and lattices (Providence, RI, 2001). Lect. Notes Comput. Sci. 2146 (2001) 146180. Springer. CrossRef
Rouault, A., Asymptotic behavior of random determinants in the Laguerre, Gram and Jacobi ensembles. ALEA Lat. Am. J. Probab. Math. Stat. 3 (2007) 181230 (electronic).
Schnorr, C.P., A hierarchy of polynomial time basis reduction algorithms. Theory of algorithms, Colloq. Pécs/Hung, 1984. Colloq. Math. Soc. János Bolyai 44 (1986) 375386.
Vallée, B., Un problème central en géométrie algorithmique des nombres : la réduction des réseaux. Autour de l'algorithme de Lenstra Lenstra Lovasz. RAIRO Inform. Théor. Appl. 3 (1989) 345376. English translation by E. Kranakis in CWI-Quarterly - 1990 - 3. CrossRef