多元整系数多项式因式分解的一种理论和算法

本文将ｔ（ｔ是大于２的整数）元整系数多项式看成为系数为ｔ－２元整系数多项式的二元多项式，建立了多元整系数多项式因式分解的一种新理论，进而得到了分解多元整系数多项式的一个有力的算法。     

A simultaneous canonical form of a pair of matrices and applications involving the weighted Moore–Penrose inverse

In this paper, a simultaneous canonical form of a pair of rectangular complex matrices is developed. Using this new tool we give a necessary and sufficient condition to assure that the reverse order law is valid for the weighted Moore–Penrose inverse. Additionally, we characterize matrices ordered by the weighted star partial order and adjacent matrices as applications.     

New classes of second order difference equations solvable by factorization method

Under some assumptions we find a general solution of the factorization problem for a family of second order difference equations.     

New representation and factorizations of the higher-order ultraspherical-type differential equations

The paper deals with the class of linear differential equations of any even order 2α+4$2\alpha +4$, α∈_N0$\alpha \in {\mathbb{N}}_0$, which are associated with the so-called ultraspherical-type polynomials. These polynomials form an orthogonal system on the interval [−1,1]$[-1,1]$ with respect to the ultraspherical weight function (1−x²)^α${(1-x^2)}^{\alpha }$ and additional point masses of equal size at the two endpoints. The differential equations of “ultraspherical-type” were developed by R. Koekoek in 1994 by utilizing special function methods. In the present paper, a new and completely elementary representation of these higher-order differential equations is presented. This result is used to deduce the orthogonality relation of the ultraspherical-type polynomials directly from the differential equation property. Moreover, we introduce two types of factorizations of the corresponding differential operators of order 2α+4$2\alpha +4$ into a product of α+2$\alpha +2$ linear second-order operators.     

Proof of factorization using background field method of QCD

Factorization theorem plays the central role at high energy colliders to study standard model and beyond standard model physics. The proof of factorization theorem is given by Collins, Soper and Sterman to all orders in perturbation theory by using diagrammatic approach. One might wonder if one can obtain the proof of factorization theorem through symmetry considerations at the lagrangian level. In this paper we provide such a proof.     

Factorization Index for Completely Positive Graphs

In this paper, we prove that the set of all factorization indices of a completely positive graph has no gaps. In other words, we give an affirmative answer to a question raised by N. Kogan and A. Berman [8] in the case of completely positive graphs. Received December 9, 1997, Accepted May 16, 2002     

图中具有某种性质的子图

设ｇ和ｆ是定义在图Ｇ的顶点集合Ｖ（Ｇ）上的整数值函数且对每个ｘ∈Ｖ（Ｇ）都有０≤ｇ（ｘ）≤ｆ（ｘ）且ｇ（ｘ）和ｆ（ｘ）为偶数。本文证明了：若Ｇ是一个（ｍｇ＋ｋ－１,ｍｆ－ｋ＋１）－图,１≤ｋ≤ｍ,Ｈ是Ｇ中一个给定的有ｋ条边的子图,则Ｇ存在一个子图Ｒ使得Ｒ有一个（ｇ,ｆ）－因子分解与Ｈ正交。     

二元整系数多项式因式分解的一种理论和算法

我们发现可以把二元多项式盾成系数为一元多项式的一元多项式来进行分解，据此，本文建立了二元整系数多项式因式分解的一种理论，提出了一个完整的分解二元整系数多项式的算法。这个算法还能很自然地推广成分解多元整系数多项式的算法。     

A bump triangular dynamic factorization algorithm for the simplex method

A dynamic factorization algorithm is developed which algebraically partitions the basis inverse in such a manner so that the simplex method can be executed from a series of small inverses and the basis itself. This partition is maintained dynamically so that the additional memory required to represent the basis inverse reduces to this series of small inverses for in-core implementations.The algorithm is intended for use in solving general large-scale linear programming problems. This new method of basis representation should permit rather large problems to be solved completely in-core.Preliminary computational experience is presented and comparisons are made with Reid's sparsity-exploiting variant of the Bartels—Golub decomposition for linear programming bases. The computational experience indicated that a significant reduction in memory requirements can usually be obtained using the dynamic factorization approach with only a slight (up to about 20%) degradation of execution time.This research was supported in part by the Air Force Office of Scientific Research, Air Force System Command, USAF, under AFOSR Contract/Grant Number AFOSR-74-2715.