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In this paper, we present an implicit Crank-Nicolson finite element (FE) scheme for solving a nonlinear Schr\"odinger-type system, which includes Schr\"odinger-Helmholz system and Schr\"odinger-Poisson system. In our numerical scheme, we…

Numerical Analysis · Mathematics 2024-05-14 Zhuoyue Zhang , Wentao Cai

This paper aims to construct structure-preserving numerical schemes for multi-dimensional space fractional Klein-Gordon-Schr\"{o}dinger equation, which are based on the newly developed partitioned averaged vector field methods. First, we…

Numerical Analysis · Mathematics 2019-11-27 Yayun Fu Wenjun Cai , Yushun Wang

This paper proposes a new class of mass or energy conservative numerical schemes for the generalized Benjamin-Ono (BO) equation on the whole real line with arbitrarily high-order accuracy in time. The spatial discretization is achieved by…

Numerical Analysis · Mathematics 2021-08-31 Kai Yang

We propose a new numerical scheme of evolution for the Einstein equations using the discrete variational derivative method (DVDM). We derive the discrete evolution equation of the constraint using this scheme and show the constraint…

General Relativity and Quantum Cosmology · Physics 2017-10-24 Takuya Tsuchiya , Gen Yoneda

In this paper, two novel linear-implicit and momentum-preserving Fourier pseudo-spectral schemes are proposed and analyzed for the regularized long-wave equation. The numerical methods are based on the blend of the Fourier pseudo-spectral…

Numerical Analysis · Mathematics 2018-09-13 Qi Hong , Yushun Wang , Yuezheng Gong

Wereportonanewmultiscalemethodapproachforthestudyofsystemswith wide separation of short-range forces acting on short time scales and long-range forces acting on much slower scales. We consider the case of the Poisson-Boltzmann equation that…

Computational Physics · Physics 2018-10-22 Giovanni Lapenta , Wei Jiang

An energy preserving reduced order model is developed for two dimensional nonlinear Schr\"odinger equation (NLSE) with plane wave solutions and with an external potential. The NLSE is discretized in space by the symmetric interior penalty…

Numerical Analysis · Mathematics 2019-01-15 Bülent Karasözen , Murat Uzunca

We propose two novel data-driven dynamic mode decomposition (DMD)-type methods, the Crank--Nicolson DMD and the semi-implicit DMD, to predict the highly oscillatory dynamics of the semiclassical Schr\"odinger equations efficiently and…

Numerical Analysis · Mathematics 2026-03-31 Yizhe Feng , Weiguo Gao , Jia Yin

Efficient and energy stable high order time marching schemes are very important but not easy to construct for the study of nonlinear phase dynamics. In this paper, we propose and study two linearly stabilized second order semi-implicit…

Numerical Analysis · Mathematics 2019-09-04 Lin Wang , Haijun Yu

The energy preserving discrete gradient methods are generalized to finite-dimensional Riemannian manifolds by definition of a discrete approximation to the Riemannian gradient, a retraction, and a coordinate center function. The resulting…

Numerical Analysis · Mathematics 2018-05-22 Elena Celledoni , Sølve Eidnes , Brynjulf Owren , Torbjørn Ringholm

In this article, a numerical simulation of two dimensional nonlinear sine-Gordon equation with Neumann boundary condition is obtained by using a composite scheme referred to as a modified cubic B spline differential quadrature method. The…

Numerical Analysis · Mathematics 2014-10-02 H. S. Shukla , Mohammad Tamsir , Vineet K. Srivastava

In this paper, we introduce and analyze a class of numerical schemes that demonstrate remarkable superiority in terms of efficiency, the preservation of positivity, energy stability, and high-order precision to solve the time-dependent…

Numerical Analysis · Mathematics 2025-07-01 Waixiang Cao , Yuzhe Qin , Minqiang Xu

We discuss structure-preserving numerical discretizations for repulsive and attractive Euler-Poisson equations that find applications in fluid-plasma and self-gravitation modeling. The scheme is fully discrete and structure preserving in…

Numerical Analysis · Mathematics 2023-05-10 Matthias Maier , John N. Shadid , Ignacio Tomas

In this paper, we propose and analyze a fully discrete finite element projection method for the magnetohydrodynamic (MHD) equations. A modified Crank--Nicolson method and the Galerkin finite element method are used to discretize the model…

Numerical Analysis · Mathematics 2022-04-13 Cheng Wang , Jilu Wang , Zeyu Xia , Liwei Xu

We present a linear, second order fully discrete numerical scheme on a staggered grid for a thermodynamically consistent hydrodynamic phase field model of binary compressible fluid flow mixtures derived from the generalized Onsager…

Numerical Analysis · Mathematics 2019-07-24 Xueping Zhao , Qi Wang

Energy-preserving numerical methods for solving the Hodge wave equation is developed in this paper. Based on the de Rham complex, the Hodge wave equation can be formulated as a first-order system and mixed finite element methods using…

Numerical Analysis · Mathematics 2020-09-08 Yongke Wu , Yanhong Bai

We design a novel, exactly energy-conserving implicit non-symplectic integration method for an eight-dimensional Hamiltonian system with four degrees of freedom. In our algorithm, each partial derivative of the Hamiltonian with respect to…

General Relativity and Quantum Cosmology · Physics 2019-12-30 Shiyang Hu , Xin Wu , Guoqing Huang , Enwei Liang

In this paper, we propose an efficient method for solving multi-dimensional Riesz space fractional diffusion equations with variable coefficients. The Crank-Nicolson (CN) method is used for temporal discretization, while the fourth-order…

Numerical Analysis · Mathematics 2025-08-01 Yuan-Yuan Huang , Wei Qu , Sean Y. Hon , Siu-Long Lei

This article focuses on an energy-conservation Galerkin finite element method (FEM) for the generalized Klein-Gordon-Zakharov (KGZ) equations. This method combines the bilinear finite element method for spatial discretization with the…

Numerical Analysis · Mathematics 2026-05-13 Xuemiao Xu , Maosheng Jiang , Jiansong Zhang , Jiang Zhu

This paper presents an energy-preserving machine learning method for inferring reduced-order models (ROMs) by exploiting the multi-symplectic form of partial differential equations (PDEs). The vast majority of energy-preserving…

Machine Learning · Computer Science 2024-09-17 Süleyman Yıldız , Pawan Goyal , Peter Benner