Efficient computation of the characteristic polynomial

J. Dumas, Clément Pernet, Z. Wan
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引用次数: 48

Abstract

We deal with the computation of the characteristic polynomial of dense matrices over word size finite fields and over the integers. We first present two algorithms for finite fields: one is based on Krylov iterates and Gaussian elimination. We compare it to an improvement of the second algorithm of Keller-Gehrig. Then we show that a generalization of Keller-Gehrig's third algorithm could improve both complexity and computational time. We use these results as a basis for the computation of the characteristic polynomial of integer matrices. We first use early termination and Chinese remaindering for dense matrices. Then a probabilistic approach, based on integer minimal polynomial and Hensel factorization, is particularly well suited to sparse and/or structured matrices.
高效计算特征多项式
我们处理了字长有限域和整数上密集矩阵特征多项式的计算。我们首先提出了两种有限域的算法:一种是基于Krylov迭代和高斯消去。我们将其与Keller-Gehrig第二种算法的改进进行了比较。然后我们证明了Keller-Gehrig的第三种算法的推广可以提高复杂度和计算时间。我们将这些结果作为计算整数矩阵特征多项式的基础。我们首先对密集矩阵使用了早终止和中文余数。然后,基于整数最小多项式和Hensel分解的概率方法特别适合于稀疏和/或结构化矩阵。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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