In this paper we present a new algorithm for Polynomial Linear System Solving (via evaluation/interpolation) with errors. In this scenario, errors can occur in the black box evaluation step. We improve the bound on the number of errors that we can correct, using techniques inspired by the decoding procedure of Interleaved Reed-Solomon Codes.

In a previous article, an implementation of lazy p-adic integers with a multiplication of quasi-linear complexity, the so-called relaxed product, was presented. Given a ring R and an element p in R, we design a relaxed Hensel lifting for algebraic systems from R/ (p) to the p-adic completion Rp of R. Thus, any root of linear and algebraic regular systems can be lifted with a quasi-optimal complexity. We report our implementations in C++ within the computer algebra system Mathemagix and compare them with Newton operator. As an application, we solve linear systems over the integers and compare the running times with Linbox and IML.

International audienceOrder bases are a fundamental tool for linear algebra with polynomial coefficients. In particular, block Wiedemann methods are nowadays able to tackle large sparse matrix problems because they benefit from fast order basis algorithms. However, such fast algorithms suffer from two practical drawbacks: they are not designed for early termination and often require more knowledge on the input than necessary. In this paper, we propose an online algorithm for order basis which allows for both early termination and minimal input requirement while keeping quasi-optimal complexity in the order. Using this algorithm inside block Wiedemann methods leads to an improvement of their practical performance by a constant factor