Ordinary reduction of K3 surfaces

Let X be a K3 surface over a number field K. We prove that there exists a finite algebraic field extension E/K such that X has ordinary reduction at every non-archimedean place of E outside a density zero set of places.      

Quadrature Based Optimal Iterative Methods with Applications in High-Precision Computing

We present a simple yet effective and applicable scheme, based on quadrature, for constructing optimal iterative methods. According to the, still unproved, Kung-Traub conjecture an optimal iterative method based on $n+1$ evaluations could achieve a maximum convergence order of $2^n$. Through quadrature, we develop optimal iterative methods of orders four and eight. The scheme can further be applied to develop iterative methods of even higher orders. Computational results demonstrate that the developed methods are efficient as compared with many well known methods.     

Multigrid Solution of a Lavrentiev-Regularized State-Constrained Parabolic Control Problem

A mesh-independent, robust, and accurate multigrid scheme to solve a linear state-constrained parabolic optimal control problem is presented. We first consider a Lavrentiev regularization of the state-constrained optimization problem. Then, a multigrid scheme is designed for the numerical solution of the regularized optimality system. Central to this scheme is the construction of an iterative pointwise smoother which can be formulated as a local semismooth Newton iteration. Results of numerical experiments and theoretical two-grid local Fourier analysis estimates demonstrate that the proposed scheme is able to solve parabolic state-constrained optimality systems with textbook multigrid efficiency.     

应用于大场景光学演示实验的高亮度白光光源制作

采用超高压汞灯为光源灯芯,制作了应用于大场景物理演示实验教学的高亮度白光光源.该光源可以用于牛顿环干涉实验和光栅衍射实验.     

利用牛顿环实验测定玻璃的弹性模量

弹性模量是衡量物体抵抗形变能力的重要物理量,本文在对牛顿环这一大学物理经典实验研究的基础之上,对牛顿环仪进行了改装,从理论上分析光学平板玻璃与平凸透镜接触端暗斑大小与外力的关系。测定弹性模量,同时利用MTALAB进行数据处理。     

Inexact Newton method via Lanczos decomposed technique for solving box-constrained nonlinear systems

This paper proposes an inexact Newton method via the Lanczos decomposed technique for solving the box-constrained nonlinear systems. An iterative direction is obtained by solving an affine scaling quadratic model with the Lanczos decomposed technique. By using the interior backtracking line search technique, an acceptable trial step length is found along this direction. The global convergence and the fast local convergence rate of the proposed algorithm are established under some reasonable conditions. Furthermore, the results of the numerical experiments show the effectiveness of the pro- posed algorithm.     

Newton Methods for Solving Two Classes of Nonsmooth Equations

The paper is devoted to two systems of nonsmooth equations. One is the system of equations of max-type functions and the other is the system of equations of smooth compositions of max-type functions. The Newton and approximate Newton methods for these two systems are proposed. The Q-superlinear convergence of the Newton methods and the Q-linear convergence of the approximate Newton methods are established. The present methods can be more easily implemented than the previous ones, since they do not require an element of Clarke generalized Jacobian, of B-differential, or of b-differential, at each iteration point.     

多重网格法与Newton-Raphson法耦合求线弹流数值解

利用多重网格算法,在最粗网格上,采用Newton-Raphson迭代法模式精解线接触弹流非线性方程组,充分利用了多重网格法与Newton-Raphson法各自的优点,计算实践表明,求解弹流问题的数值解过程在收敛与稳定性方面均有较大改善,且有相当宽的载荷参数适用范围。     

Theoretical Efficiency of an Inexact Newton Method

We propose a local algorithm for smooth unconstrained optimization problems with n variables. The algorithm is the optimal combination of an exact Newton step with Choleski factorization and several inexact Newton steps with preconditioned conjugate gradient subiterations. The preconditioner is taken as the inverse of the Choleski factorization in the previous exact Newton step. While the Newton method is converging precisely with Q-order 2, this algorithm is also precisely converging with Q-order 2. Theoretically, its average number of arithmetic operations per step is much less than the corresponding number of the Newton method for middle-scale and large-scale problems. For instance, when n=200, the ratio of these two numbers is less than 0.53. Furthermore, the ratio tends to zero approximately at a rate of log 2/logn when n approaches infinity.