计算矩阵函数双线性形式的Krylov子空间算法的误差分析

矩阵函数的双线性形式u^Tf（A）v出现在很多应用问题中,其中u,v ∈ Rⁿ,A ∈ R^n×n,f（z）为给定的解析函数.开发其有效可靠的数值算法一直是近年来学术界所关注的问题,其中关于其数值算法的停机准则多种多样,但欠缺理论支持,可靠性存疑.本文将对矩阵函数的双线性形式u^Tf（A）v的数值算法和后验误差估计进行研究,给出其基于Krylov子空间算法的误差分析,导出相应的误差展开式,证明误差展开式的首项是一个可靠的后验误差估计,据此可以为算法设计出可靠的停机准则.     

On density of transitive operator algebras

In this paper we study the transitive algebra question by considering the invariant subspace problem relative to von Neumann algebras. We prove that the algebra (not necessarily ∗) generated by a pair of sums of two unitary generators of L(F_∞) and its commutant is strong-operator dense in B(H). The relations between the transitive algebra question and the invariant subspace problem relative to some von Neumann algebras are discussed.     

An improved GPBi-CG algorithm suitable for distributed parallel computing

An improved generalized product-type bi-conjugate gradient (GPBi-CG) method (IGPBi-CG method, in brief) for solving large sparse linear systems with unsymmetrical coefficient matrices is proposed for distributed parallel environments. The method reduces three global synchronization points to two by reconstructing GPBi-CG method and the communication time required for the inner product can be efficiently overlapped with useful computation. The cost is only slightly increased computation time, which can be ignored compared with the reduction of communication time. Performance and isoefficiency analysis show that the IGPBi-CG method has better parallelism and scalability than the GPBi-CG method. Numerical experiments show that the scalability can be improved by a factor greater than 1.5 and the improvement in parallel communication performance approaches 33.3˙%.     

A block inverse-free preconditioned Krylov subspace method for symmetric generalized eigenvalue problems

The inverse-free preconditioned Krylov subspace method of Golub and Ye [G.H. Golub, Q. Ye, An inverse free preconditioned Krylov subspace method for symmetric generalized eigenvalue problems, SIAM J. Sci. Comp. 24 (2002) 312-334] is an efficient algorithm for computing a few extreme eigenvalues of the symmetric generalized eigenvalue problem. In this paper, we first present an analysis of the preconditioning strategy based on incomplete factorizations. We then extend the method by developing a block generalization for computing multiple or severely clustered eigenvalues and develop a robust black-box implementation. Numerical examples are given to illustrate the analysis and the efficiency of the block algorithm.     

A numerical solution of the constrained weighted energy problem

A numerical algorithm is presented to solve the constrained weighted energy problem from potential theory. As one of the possible applications of this algorithm, we study the convergence properties of the rational Lanczos iteration method for the symmetric eigenvalue problem. The constrained weighted energy problem characterizes the region containing those eigenvalues that are well approximated by the Ritz values. The region depends on the distribution of the eigenvalues, on the distribution of the poles, and on the ratio between the size of the matrix and the number of iterations. Our algorithm gives the possibility of finding the boundary of this region in an effective way.We give numerical examples for different distributions of poles and eigenvalues and compare the results of our algorithm with the convergence behavior of the explicitly performed rational Lanczos algorithm.     

Approximation of the linear combination of $\varphi$-functions using the block shift-and-invert Krylov subspace method

In this paper, we develop an algorithm in which the block shift-and-invert Krylov subspace method can be employed for approximating the linear combination of the matrix exponential and related exponential-type functions. Such evaluation plays a major role in a class of numerical methods known as exponential integrators. We derive a low-dimensional matrix exponential to approximate the objective function based on the block shift-and-invert Krylov subspace methods. We obtain the error expansion of the approximation, and show that the variants of its first term can be used as reliable a posteriori error estimates and correctors. Numerical experiments illustrate that the error estimates are efficient and the proposed algorithm is worthy of further study.     

一类具有两个非线性控制项的系统绝对稳定的充要性条件

本文给出一类具有两个非线性控制项的系统绝对稳定的充要性判据.该判据关于未定常数均是线性的,易于检验,且有较广适用范围.     

算子子空间的渐近自反性和遗传性

研究了算子子空间的渐近自反性问题，渐近自反子空间的遗传斯近自反性以及某些单个算子的渐近自反性．我们也讨论了投影网类的浙近自反性。     

Absolute continuity of operator-self-decomposable distributions on R

It is shown that every genuinely d-dimensional operator-self-decomposable distribution is absolutely continuous.