多项式近似因式分解的可信验证
The Verification of Approximate Polynomial Factorization
DOI: 10.12677/AAM.2020.98144, PDF,    科研立项经费支持
作者: 严杰煜, 李 喆*:长春理工大学理学院,吉林 长春
关键词: 多元多项式近似因式分解可信验证Multivariate Polynomial Approximate Factorization Verification
摘要: 众所周知,系数有扰动多项式的因式分解是不连续的。因此,传统的多项式因式分解对于数值计算来说是一个不适定问题。本文利用区间算法,研究多项式近似因式分解的可信计算。给定一个实多项式,本文利用已有算法计算给定多项式其因式分解流形结构,设计算法输出在该因式分解流形结构中一系数为区间的因式分解。算法保证,在该区间因式分解中存在一系数为实数的因式分解,其所对应的多项式为在确定的因式分解流形结构中与给定多项式残差最小的多项式。
Abstract: It is well-known for a polynomial with perturbed coefficients, its factorization is discontinuous. Therefore, the traditional polynomial factorization is an ill-posed problem for numerical computation. This paper is to study the trusted computing of polynomial approximate factorization on the basis of interval algorithm. Given a polynomial of real coefficients, this paper uses the existing algorithm to compute the structure of factorization manifold, and provides a verification algorithm to compute a factorization with interval coefficients in the computed factorization manifold structure. The algorithm is guaranteed that there exists a real factorization within this interval factorization such that the corresponding polynomial of the real factorization is the polynomial with the minimum residual in the computed decomposition manifold structure.
文章引用:严杰煜, 李喆. 多项式近似因式分解的可信验证[J]. 应用数学进展, 2020, 9(8): 1230-1238. https://doi.org/10.12677/AAM.2020.98144

参考文献

[1] Lenstra, A., Lenstra, H. and Lovasz, L. (1982) Factoring Polynomials with Rational Coefficients. Mathematische Annalen, 261, 515-534. [Google Scholar] [CrossRef
[2] Von zur Gathen, J. and Kaltofen, E. (1985) Factoring Sparse Multivariate Polynomials. Journal of Computer and System Sciences, 31, 265-287. [Google Scholar] [CrossRef
[3] Kaltofen, E. (1985) Polynomial-Time Reductions from Multivariate to Bi- and Univariate Integral Polynomial Factorization. SIAM Journal on Computing, 14, 469-489. [Google Scholar] [CrossRef
[4] Lecerf, G. (2010) New Recombination Algorithms for Bivariate Polynomial Factorization Based on Hensel Lifting. Applicable Algebra in Engineering, Communication and Computing, 21, 151-176. [Google Scholar] [CrossRef
[5] Gao, S. (2003) Factoring Multivariate Polynomials via Partial Differential Equations. Mathematics of Computation, 72, 801-822. [Google Scholar] [CrossRef
[6] Ruppert, W. (1999) Reducibility of Polynomials f(x, y) Modulo p. Journal of Number Theory, 77, 62-70. [Google Scholar] [CrossRef
[7] Sasaki, T. (2001) Approximate Multivariate Polynomial Factorization Based on Zero-Sum Relations. In: Proceedings of ISSAC 2001, ACM Press, New York, 284-291. [Google Scholar] [CrossRef
[8] Gao, S., Kaltofen, E., May, J., Yang, Z. and Zhi, L. (2004) Approximate Factorization of Multivariate Polynomials via Differential Equations. In: Proc. ISSAC’04, ACM Press, New York, 167-174. [Google Scholar] [CrossRef
[9] Kaltofen, E., May, J., Yang, Z. and Zhi, L. (2008) Approximate Factorization of Multivariate Polynomials Using Singular Value Decomposition. Journal of Symbolic Computation, 43, 359-376. [Google Scholar] [CrossRef
[10] Corless, R., Giesbrecht, M., Van Hoeij, M., Kotsireas, I. and Watt, S. (2001) Towards Factoring Bivariate Approximate Polynomials. In: Proc. of ISSAC’01, ACM Press, New York, 85-92. [Google Scholar] [CrossRef
[11] Corless, R., Galligo, A., Kotsireas, I. and Watt, S. (2002) A Geometric-Numeric Algorithm for Absolute Factorization of Multivariate Polynomials. In: Proc. of ISSAC’02, ACM Press, New York, 37-45. [Google Scholar] [CrossRef
[12] Galligo, A. and Van Hoeij, M. (2007) Approximate Bivariate Factorization, a Geometric Viewpoint. In: Proceedings of SNC’07, ACM Press, New York, 1-10.
[13] Kahan, W. (1972) Conserving Confluence Curbs Ill-Condition. Technical Report, Computer Science Department, University of California, Berkeley.
[14] Wu, W.Y. and Zeng, Z.G. (2017) The Numerical Factorization of Polynomials. Foundations of Computational Mathematics, 17, 259-286. [Google Scholar] [CrossRef
[15] Galligo, A. and Watt, S. (1997) A Numerical Absolute Primality Test for Bivariate Polynomials. In: Proceedings of ISSAC97, ACM Press, New York, 217-224. [Google Scholar] [CrossRef
[16] Rump, S.M. (1999) INTLAB-Interval Laboratory. Springer Netherlands, Berlin. [Google Scholar] [CrossRef
[17] Rump, S.M. (1983) Solving Algebraic Problems with High Accuracy. In: Kulisch, W.L. and Miranker, W.L., Eds., A New Approach to Scientific Computation, Academic Press, San Diego, 51-120. [Google Scholar] [CrossRef