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Related papers: Gr\"obner Bases and Generation of Difference Schem…

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We develop a method for generating solutions to large classes of evolutionary partial differential systems with nonlocal nonlinearities. For arbitrary initial data, the solutions are generated from the corresponding linearized equations.…

Analysis of PDEs · Mathematics 2018-05-09 Margaret Beck , Anastasia Doikou , Simon J. A. Malham , Ioannis Stylianidis

We present a number of new contributions to the topic of constructing efficient higher-order splitting methods for the numerical integration of evolution equations. Particular schemes are constructed via setup and solution of polynomial…

Numerical Analysis · Mathematics 2016-04-06 Winfried Auzinger , Harald Hofstätter , David Ketcheson , Othmar Koch

We present a natural framework for constructing energy-stable time discretization schemes. By leveraging the Onsager principle, we demonstrate its efficacy in formulating partial differential equation models for diverse gradient flow…

Numerical Analysis · Mathematics 2024-10-16 Huangxin Chen , Hailiang Liu , Xianmin Xu

In this study, we examine numerical approximations for 2nd-order linear-nonlinear differential equations with diverse boundary conditions, followed by the residual corrections of the first approximations. We first obtain numerical results…

Numerical Analysis · Mathematics 2023-06-19 Shovan Sourav Datta Pranta , Md. Shafiqul Islam

The dynamic algorithm to compute a Gr\"obner basis is nearly twenty years old, yet it seems to have arrived stillborn; aside from two initial publications, there have been no published followups. One reason for this may be that, at first…

Commutative Algebra · Mathematics 2014-02-18 Massimo Caboara , John Perry

In this paper we propose an algorithm for the numerical solution of arbitrary differential equations of fractional order. The algorithm is obtained by using the following decomposition of the differential equation into a system of…

Numerical Analysis · Mathematics 2025-10-20 Leszczynski Jacek , Ciesielski Mariusz

A development of an inverse first-order divided difference operator for functions of several variables is presented. Two generalized derivative-free algorithms builded up from Ostrowski's method for solving systems of nonlinear equations…

Numerical Analysis · Mathematics 2011-10-12 Miquel Grau-Sánchez , Miquel Noguera , Sergio Amat

We present a generative reduced basis (RB) approach to construct reduced order models for parametrized partial differential equations. Central to this approach is the construction of generative RB spaces that provide rapidly convergent…

Numerical Analysis · Mathematics 2024-10-08 Ngoc Cuong Nguyen

We consider regular polynomial interpolation algorithms on recursively defined sets of interpolation points which approximate global solutions of arbitrary well-posed systems of linear partial differential equations. Convergence of the…

Numerical Analysis · Mathematics 2008-07-10 Joerg Kampen

Robust and convergent high-order numerical methods for solving partial differential equations are highly attractive due to their efficiency on modern and next-generation hardware architectures. However, designing such methods for nonlinear…

Numerical Analysis · Mathematics 2026-03-24 Dougal Stewart , Nathan Lee , Kenneth Duru

The implicit compact finite-difference scheme was developed for evolutionary partial differential parabolic and Schr\"odinger-type equations and systems with a weak nonlinearity. To make a temporal step of the compact implicit scheme we…

Mathematical Physics · Physics 2018-12-31 Vladimir Gordin , Evgenii Tsymbalov

The proximal Galerkin finite element method is a high-order, low-iteration complexity, nonlinear numerical method that preserves the geometric and algebraic structure of point-wise bound constraints in infinite-dimensional function spaces.…

Numerical Analysis · Mathematics 2024-12-18 Brendan Keith , Thomas M. Surowiec

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

I introduce an innovative methodology for deriving numerical models of systems of partial differential equations which exhibit the evolution of spatial patterns. The new approach directly produces a discretisation for the evolution of the…

Numerical Analysis · Mathematics 2025-10-20 A. J. Roberts

The aim of this paper is to apply a high-order discontinuous-in-time scheme to second-order hyperbolic partial differential equations (PDEs). We first discretize the PDEs in time while keeping the spatial differential operators…

Numerical Analysis · Mathematics 2021-11-30 Aili Shao

This paper studies a new class of integration schemes for the numerical solution of semi-explicit differential-algebraic equations of differentiation index 2 in Hessenberg form. Our schemes provide the flexibility to choose different…

Numerical Analysis · Mathematics 2021-04-14 Robert Altmann , Roland Herzog

In this work, we introduce semi-implicit or implicit finite difference schemes for the continuity equation with a gradient flow structure. Examples of such equations include the linear Fokker-Planck equation and the Keller-Segel equations.…

Numerical Analysis · Mathematics 2022-03-25 Jingwei Hu , Xiangxiong Zhang

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

There are several well-established approaches to constructing finite difference schemes that preserve global invariants of a given partial differential equation. However, few of these methods preserve more than one conservation law locally.…

Numerical Analysis · Mathematics 2021-10-19 Gianluca Frasca-Caccia , Peter E. Hydon

We present a structure-preserving Eulerian algorithm for solving $L^2$-gradient flows and a structure-preserving Lagrangian algorithm for solving generalized diffusions. Both algorithms employ neural networks as tools for spatial…

Numerical Analysis · Mathematics 2024-04-16 Ziqing Hu , Chun Liu , Yiwei Wang , Zhiliang Xu
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