Abstract

An algorithm which either finds an nonzero integer vector m{\mathbf m} for given tt real nn-dimensional vectors x1,...,xt{\mathbf x}_1,...,{\mathbf x}_t such that xiTm=0{\mathbf x}_i^T{\mathbf m}=0 or proves that no such integer vector with norm less than a given bound exists is presented in this paper. The cost of the algorithm is at most O(n4+n3log⁡λ(X)){\mathcal O}(n^4 + n^3 \log λ(X)) exact arithmetic operations in dimension nn and the least Euclidean norm λ(X)λ(X) of such integer vectors. It matches the best complexity upper bound known for this problem. Experimental data show that the algorithm is better than an already existing algorithm in the literature. In application, the algorithm is used to get a complete method for finding the minimal polynomial of an unknown complex algebraic number from its approximation, which runs even faster than the corresponding \emph{Maple} built-in function.

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