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Differential complexes such as the de Rham complex have recently come to play an important role in the design and analysis of numerical methods for partial differential equations. The design of stable discretizations of systems of partial…

Numerical Analysis · Mathematics 2025-10-20 Douglas N. Arnold

Two-fluid plasma flow equations describe the flow of ions and electrons with different densities, velocities, and pressures. We consider the ideal plasma flow i.e. we ignore viscous, resistive, and collision effects. The resulting system of…

Numerical Analysis · Mathematics 2024-09-25 Jaya Agnihotri , Deepak Bhoriya , Harish Kumar , Praveen Chandrashekhar , Dinshaw S. Balsara

We study the Crank-Nicolson scheme for stochastic differential equations (SDEs) driven by multidimensional fractional Brownian motion $(B^{1}, \dots, B^{m})$ with Hurst parameter $H \in (\frac 12,1)$. It is well-known that for ordinary…

Probability · Mathematics 2017-09-07 Yaozhong Hu , Yanghui Liu , David Nualart

High-order entropy-stable discontinuous Galerkin methods for the compressible Euler and Navier-Stokes equations require the positivity of thermodynamic quantities in order to guarantee their well-posedness. In this work, we introduce a…

Numerical Analysis · Mathematics 2023-01-04 Yimin Lin , Jesse Chan , Ignacio Tomas

We construct a nonstandard finite difference numerical scheme to approximate stochastic differential equations (SDEs) using the idea of weighed step introduced by R.E. Mickens. We prove the strong convergence of our scheme under locally…

Numerical Analysis · Mathematics 2015-07-23 Frédéric Pierret

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

Traditional numerical techniques for solving time-dependent partial-differential-equation (PDE) initial-value problems (IVPs) store a truncated representation of the function values and some number of their time derivatives at each time…

Numerical Analysis · Mathematics 2011-09-08 Hal Finkel

We propose some finite element schemes to solve a class of fourth-order nonlinear PDEs, which include the vector-valued Landau--Lifshitz--Baryakhtar equation, the Swift--Hohenberg equation, and various Cahn--Hilliard-type equations with…

Numerical Analysis · Mathematics 2024-11-19 Agus L. Soenjaya , Thanh Tran

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

We propose and analyze a linearly stabilized semi-implicit diffusive Crank--Nicolson scheme for the Cahn--Hilliard gradient flow. In this scheme, the nonlinear bulk force is treated explicitly with two second-order stabilization terms. This…

Numerical Analysis · Mathematics 2020-04-14 Lin Wang , Haijun Yu

This paper deals with the numerical solution of conservation laws in the two dimensional case using a novel compact implicit time discretization that enables applications of fast algebraic solvers. We present details for the second order…

Numerical Analysis · Mathematics 2025-12-16 Peter Frolkovic , Dagmar Zakova

Stochastic Klein--Gordon--Schr\"odinger (KGS) equations are important mathematical models and describe the interaction between scalar nucleons and neutral scalar mesons in the stochastic environment. In this paper, we propose novel…

Numerical Analysis · Mathematics 2023-05-19 Jialin Hong , Baohui Hou , Liying Sun , Xiaojing Zhang

Stochastic Klein--Gordon--Schr\"odinger (KGS) equations are important mathematical models and describe the interaction between scalar nucleons and neutral scalar mesons in the stochastic environment. In this paper, we propose novel…

Numerical Analysis · Mathematics 2023-05-19 Jialin Hong , Baohui Hou , Liying Sun , Xiaojing Zhang

This paper establishes a discretization scheme for a large class of stochastic differential equations driven by a time-changed Brownian motion with drift, where the time change is given by a general inverse subordinator. The scheme involves…

Probability · Mathematics 2015-11-13 Ernest Jum , Kei Kobayashi

Nonconservative evolution problems describe irreversible processes and dissipative effects in a broad variety of phenomena. Such problems are often characterised by a conservative part, which can be modelled as a Hamiltonian term, and a…

Numerical Analysis · Mathematics 2025-05-12 Damiano Lombardi , Cecilia Pagliantini

Many successful methods to learn dynamical systems from data have recently been introduced. However, ensuring that the inferred dynamics preserve known constraints, such as conservation laws or restrictions on the allowed system states,…

Machine Learning · Computer Science 2024-02-16 Alistair White , Niki Kilbertus , Maximilian Gelbrecht , Niklas Boers

In this paper, we present and analyze fully discrete finite difference schemes designed for solving the initial value problem associated with the fractional Korteweg-de Vries (KdV) equation involving the fractional Laplacian. We design the…

Numerical Analysis · Mathematics 2024-03-14 Mukul Dwivedi , Tanmay Sarkar

Von Neumann established that discretized algebraic equations must be consistent with the differential equations, and must be stable in order to obtain convergent numerical solutions for the given differential equations. The "stability" is…

Numerical Analysis · Mathematics 2012-05-31 Lun-Shin Yao

This paper is concerned with the Einstein equations in axisymmetric vacuum spacetimes. We consider numerical evolution schemes that solve the constraint equations as well as elliptic gauge conditions at each time step. We examine two such…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Oliver Rinne

We propose an accurate data-driven numerical scheme to solve Stochastic Differential Equations (SDEs), by taking large time steps. The SDE discretization is built up by means of a polynomial chaos expansion method, on the basis of…

Numerical Analysis · Mathematics 2021-09-24 Shuaiqiang Liu , Lech A. Grzelak , Cornelis W. Oosterlee
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