Modelling the LLL Algorithm by Sandpiles

نویسندگان

  • Manfred G. Madritsch
  • Brigitte Vallée
چکیده

The LLL algorithm aims at finding a “reduced” basis of a Euclidean lattice. The LLL algorithm plays a primary role in many areas of mathematics and computer science. However, its general behaviour is far from being well understood. There are already many experimental observations about the number of iterations or the geometry of the output, that pose challenging questions that remain unanswered and lead to natural conjectures which are yet to be proved. However, until now, there exist few experimental observations about the precise execution of the algorithm. Here, we provide experimental results which precisely describe an essential parameter of the execution, namely the “logarithm of the decreasing ratio”. These experiments give arguments towards a “regularity” hypothesis (R). Then, we propose a simplified model for the LLL algorithm, based on the hypothesis (R), which leads us to discrete dynamical systems, namely sandpiles models. It is then possible to obtain a precise quantification of the main parameters of the LLL algorithm. These results fit the experimental results performed on general input bases, which indirectly substantiates the validity of such a regularity hypothesis and shows the usefulness of such a simplified model.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A modified LLL algorithm for change of ordering of Grobner basis

In this paper, a modied version of LLL algorithm, which is a an algorithm with output-sensitivecomplexity, is presented to convert a given Grobner basis with respect to a specic order of a polynomialideal I in arbitrary dimensions to a Grobner basis of I with respect to another term order.Also a comparison with the FGLM conversion and Buchberger method is considered.

متن کامل

A Robust Feedforward Active Noise Control System with a Variable Step-Size FxLMS Algorithm: Designing a New Online Secondary Path Modelling Method

Several approaches have been introduced in literature for active noise control (ANC)systems. Since Filtered-x-Least Mean Square (FxLMS) algorithm appears to be the best choice as acontroller filter. Researchers tend to improve performance of ANC systems by enhancing andmodifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANCapplications an online secondary pat...

متن کامل

Segment LLL Reduction of Lattice Bases Using Modular Arithmetic

The algorithm of Lenstra, Lenstra, and Lovász (LLL) transforms a given integer lattice basis into a reduced basis. Storjohann improved the worst case complexity of LLL algorithms by a factor of O(n) using modular arithmetic. Koy and Schnorr developed a segment-LLL basis reduction algorithm that generates lattice basis satisfying a weaker condition than the LLL reduced basis with O(n) improvemen...

متن کامل

Numerical Properties of the LLL Algorithm

The LLL algorithm is widely used to solve the integer least squares problems that arise in many engineering applications. As most practitioners did not understand how the LLL algorithm works, they avoided the issue by referring to the method as an integer Gram Schmidt approach (without explaining what they mean by this term). Luk and Tracy were first to describe the behavior of the LLL algorith...

متن کامل

N-Dimensional LLL Reduction Algorithm with Pivoted Reflection

The Lenstra-Lenstra-Lovász (LLL) lattice reduction algorithm and many of its variants have been widely used by cryptography, multiple-input-multiple-output (MIMO) communication systems and carrier phase positioning in global navigation satellite system (GNSS) to solve the integer least squares (ILS) problem. In this paper, we propose an n-dimensional LLL reduction algorithm (n-LLL), expanding t...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2010