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Featured researches published by Kai Zhang.


Advances in Computational Mathematics | 2009

Studies on some perfectly matched layers for one-dimensional time-dependent systems

Yanping Lin; Kai Zhang; Jun Zou

We will analyze some perfectly matched layers (PMLs) for the one-dimensional time-dependent Maxwell system, acoustic equations and hyperbolic systems in unbounded domains. The exponential decays and convergence of the PML solutions are studied. Some finite difference schemes are proposed for the PML equations and their stability and convergence are established.


Applied Mathematics and Computation | 2016

Multi-level Monte Carlo weak Galerkin method for elliptic equations with stochastic jump coefficients

Jingshi Li; Xiaoshen Wang; Kai Zhang

In this paper, we present a multi-level Monte Carlo weak Galerkin method for solving elliptic equations with stochastic jump coefficients. The multi-level Monte Carlo technique balances the spatial approximation error and the sampling error. The weak Galerkin technique is a stable and high-order accurate method which can easily handle deterministic partial differential equations with complex geometries or jump coefficients given by each sample, and this method is also able to capture highly complex solutions exhibiting discontinuities or oscillations with high resolution. Comparing with the standard Monte Carlo method, by using the multi-level Monte Carlo weak Galerkin method, the computational cost can be sharply reduced to log-linear complexity with respect to the degree of freedom in spatial direction. The numerical experiments verify the efficiency of our algorithms.


Applicable Analysis | 2015

Front-fixing FEMs for the pricing of American options based on a PML technique

Kai Zhang; Haiming Song; Jingzhi Li

In this paper, efficient numerical methods are developed for the pricing of American options governed by the Black–Scholes equation. The front-fixing technique is first employed to transform the free boundary of optimal exercise prices to some a priori known temporal line for a one-dimensional parabolic problem via the change of variables. The perfectly matched layer (PML) technique is then applied to the pricing problem for the effective truncation of the semi-infinite domain. Finite element methods using the respective continuous and discontinuous Galerkin discretization are proposed for the resulting truncated PML problems related to the options and Greeks. The free boundary is determined by Newton’s method coupled with the discrete truncated PML problem. Stability and nonnegativeness are established for the approximate solution to the truncated PML problem. Under some weak assumptions on the PML medium parameters, it is also proved that the solution of the truncated PML problem converges to that of the unbounded Black–Scholes equation in the computational domain and decays exponentially in the perfectly matched layer. Numerical experiments are conducted to test the performance of the proposed methods and to compare them with some existing methods.


Numerical Algorithms | 2018

An efficient alternating direction method of multipliers for optimal control problems constrained by random Helmholtz equations

Jingshi Li; Xiaoshen Wang; Kai Zhang

Based on the alternating direction method of multipliers (ADMM), we develop three numerical algorithms incrementally for solving the optimal control problems constrained by random Helmholtz equations. First, we apply the standard Monte Carlo technique and finite element method for the random and spatial discretization, respectively, and then ADMM is used to solve the resulting system. Next, combining the multi-modes expansion, Monte Carlo technique, finite element method, and ADMM, we propose the second algorithm. In the third algorithm, we preprocess certain quantities before the ADMM iteration, so that nearly no random variable is in the inner iteration. This algorithm is the most efficient one and is easy to implement. The error estimates of these three algorithms are established. The numerical experiments verify the efficiency of our algorithms.


Applied Geophysics | 2016

Magnetic interface forward and inversion method based on Padé approximation

Chong Zhang; Danian Huang; Kai Zhang; Yi-Tao Pu; Ping Yu

The magnetic interface forward and inversion method is realized using the Taylor series expansion to linearize the Fourier transform of the exponential function. With a large expansion step and unbounded neighborhood, the Taylor series is not convergent, and therefore, this paper presents the magnetic interface forward and inversion method based on Padé approximation instead of the Taylor series expansion. Compared with the Taylor series, Padé’s expansion’s convergence is more stable and its approximation more accurate. Model tests show the validity of the magnetic forward modeling and inversion of Padé approximation proposed in the paper, and when this inversion method is applied to the measured data of the Matagami area in Canada, a stable and reasonable distribution of underground interface is obtained.


Ima Journal of Numerical Analysis | 2006

Multi-symplectic Runge–Kutta-type methods for Hamiltonian wave equations

Hongyu Liu; Kai Zhang


Computer Methods in Applied Mechanics and Engineering | 2013

A goal-oriented error estimator for the analysis of simplified designs

Ming Li; Shuming Gao; Kai Zhang


Numerical Mathematics-theory Methods and Applications | 2017

Finite Element and Discontinuous Galerkin Methods with Perfect Matched Layers for American Options

Haiming Song; Kai Zhang; Yutian Li


East Asian Journal on Applied Mathematics | 2017

Primal-Dual Active Set Method for American Lookback Put Option Pricing

Haiming Song; Xiaoshen Wang; Kai Zhang; Qi Zhang


Communications in Computational Physics | 2016

Estimation of Impacts of Removing Arbitrarily Constrained Domain Details to the Analysis of Incompressible Fluid Flows

Kai Zhang; Ming Li; Jingzhi Li

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Xiaoshen Wang

University of Arkansas at Little Rock

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Jingzhi Li

South University of Science and Technology of China

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Yi-Tao Pu

China National Petroleum Corporation

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