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Roundoff-Error-Free Algorithms for Solving Linear Systems via Cholesky and LU Factorizations

机译:通过Cholesky和LU分解求解线性系统的无舍入误差算法

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LU and Cholesky factorizations are computational tools for efficiently solving linear systems that play a central role in solving linear programs and several other classes of mathematical programs. In many documented cases, however, the roundoff errors accrued during the construction and implementation of these factorizations lead to the misclassification of feasible problems as infeasible and vice versa. Hence, reducing these roundoff errors or eliminating them altogether is imperative to guarantee the correctness of the solutions provided by optimization solvers. To achieve this goal without having to use rational arithmetic, we introduce two roundoff-error-free factorizations that require storing the same number of individual elements and performing a similar number of operations as the traditional LU and Cholesky factorizations. Additionally, we present supplementary roundoff-error-free forward and backward substitution algorithms, thereby providing a complete tool set for solving systems of linear equations exactly and efficiently. An important property shared by the featured factorizations and substitution algorithms is that their individual coefficients' maximum word length-i.e., the maximum number of digits required for expression-is bounded polynomially. Unlike the rational arithmetic methods used in practice to solve linear systems exactly, however, the algorithms herein presented do not require any gcd calculations to bound the entries' word length. We also derive various other related theoretical results, including the total computational complexity of all the roundoff-error-free processes herein presented.
机译:LU和Cholesky因子分解是用于有效求解线性系统的计算工具,这些系统在求解线性程序和其他几种数学程序中起着核心作用。但是,在许多有案可查的案例中,在构建和实施这些因式分解过程中产生的舍入误差导致将可行问题分类为不可行,反之亦然。因此,必须减少这些舍入误差或完全消除它们,以保证优化求解器提供的解决方案的正确性。为了实现此目标而不必使用有理算术,我们引入了两个无舍入错误的因式分解,与传统的LU和Cholesky因式分解一样,它们需要存储相同数量的单个元素并执行相似数量的运算。此外,我们提出了无舍入误差的正向和反向补充算法,从而提供了一个精确而有效地求解线性方程组的完整工具集。特征分解和替换算法共享的一个重要属性是它们的各个系数的最大单词长度(即表达式所需的最大位数)是多项式有界的。但是,与实际中用于精确求解线性系统的有理算术方法不同,本文介绍的算法不需要任何gcd计算来限制条目的字长。我们还得出了其他各种相关的理论结果,包括本文介绍的所有舍入无误差过程的总计算复杂度。

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