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首页> 外文期刊>SIAM Journal on Numerical Analysis >A NUMERICAL LOCAL DIMENSION TEST FOR POINTS ON THE SOLUTION SET OF A SYSTEM OF POLYNOMIAL EQUATIONS
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A NUMERICAL LOCAL DIMENSION TEST FOR POINTS ON THE SOLUTION SET OF A SYSTEM OF POLYNOMIAL EQUATIONS

机译:多项式方程组解集上点的数值局部维检验

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摘要

The solution set V of a polynomial system, i.e., the set of common zeroes of a set of multivariate polynomials with complex coefficients, may contain several components, e. g., points, curves, surfaces, etc. Each component has attached to it a number of quantities, one of which is its dimension. Given a numerical approximation to a point p on the set V, this article presents an efficient algorithm to compute the maximum dimension of the irreducible components of V which pass through p, i.e., a local dimension test. Such a test is a crucial element in the homotopy-based numerical irreducible decomposition algorithms of Sommese, Verschelde, and Wampler. This article presents computational evidence to illustrate that the use of this new algorithm greatly reduces the cost of so-called "junk-point filtering," previously a significant bottleneck in the computation of a numerical irreducible decomposition. For moderate size examples, this results in well over an order of magnitude improvement in the computation of a numerical irreducible decomposition. As the computation of a numerical irreducible decomposition is a fundamental backbone operation, gains in efficiency in the irreducible decomposition algorithm carry over to the many computations which require this decomposition as an initial step. Another feature of a local dimension test is that one can now compute the irreducible components in a prescribed dimension without first computing the numerical irreducible decomposition of all higher dimensions. For example, one may compute the isolated solutions of a polynomial system without having to carry out the full numerical irreducible decomposition.
机译:多项式系统的解集V,即具有复数系数的一组多元多项式的公共零集,可以包含多个分量,例如例如,点,曲线,表面等。每个组件都具有许多数量,其中之一就是其尺寸。给定在集合V上点p的数值近似值,本文提出一种有效的算法来计算通过p的V的不可约分量的最大尺寸,即局部尺寸测试。这样的测试对于Sommese,Verschelde和Wampler基于同伦的数值不可约分解算法至关重要。本文提供了计算证据,以说明此新算法的使用大大降低了所谓的“垃圾点过滤”的成本,该垃圾点过滤以前是计算数值不可约分解的重要瓶颈。对于中等大小的示例,这在数值不可约分解的计算中大大提高了一个数量级。由于数值不可约分解的计算是基本的骨干运算,因此不可约分解算法中效率的提高会延续到许多需要将此分解作为初始步骤的计算中。局部维数测试的另一个特征是,现在可以在指定维数下计算不可约分量,而无需先计算所有更高维的不可约数的分解。例如,可以计算多项式系统的孤立解,而不必执行完整的数值不可约分解。

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