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We prove strong convergence of a semi-discrete finite difference method for the KdV and modified KdV equations. We extend existing results to non-smooth data (namely, in $L^2$), without size restrictions. Our approach uses a fourth order…

Numerical Analysis · Mathematics 2012-02-07 Paulo Amorim , Mário Figueira

Discrete gradient methods are geometric integration techniques that can preserve the dissipative structure of gradient flows. Due to the monotonic decay of the function values, they are well suited for general convex and nonconvex…

Optimization and Control · Mathematics 2024-07-17 Matthias J. Ehrhardt , Erlend S. Riis , Torbjørn Ringholm , Carola-Bibiane Schönlieb

We study the convergence rates of the semi-discrete (SD) method originally proposed in Halidias (2012), Semi-discrete approximations for stochastic differential equations and applications, International Journal of Computer Mathematics,…

Numerical Analysis · Mathematics 2020-05-06 Ioannis S. Stamatiou , Nikolaos Halidias

We present a novel approach for high-order accurate numerical differentiation on unstructured meshes of quadrilateral elements. To differentiate a given function, an auxiliary function with greater smoothness properties is defined which…

Numerical Analysis · Mathematics 2022-05-11 Yulong Pan , Per-Olof Persson

The article considers the discrete analogue of the method of quickest descent for an inverse Acoustics problem in case of a smooth source. The authors derived the gradient of functional in differential and discrete cases, described the…

Computational Engineering, Finance, and Science · Computer Science 2016-01-19 G. Tyulepberdinova , G. Gaziz , N. Kerimbayev , S. Abdykarimova

We present a discontinuous finite element method for the shallow water equations which exploits high-resolution realistic bathymetry data without any regularity assumption, also in the case of high-order discretizations. We prove a number…

Computational Engineering, Finance, and Science · Computer Science 2026-05-21 Luca Arpaia , Giuseppe Orlando , Christian Ferrarin , Luca Bonaventura

Discrete numerical methods with finite time-steps represent a practical technique to solve initial-value problems involving nonlinear differential equations. These methods seem particularly useful to the study of chaos since no analytical…

Chaotic Dynamics · Physics 2010-01-01 Lun-Shin Yao

We propose an extension of the discretization approaches for multilayer shallow water models, aimed at making them more flexible and efficient for realistic applications to coastal flows. A novel discretization approach is proposed, in…

Numerical Analysis · Mathematics 2018-04-18 Luca Bonaventura , Enrique D. Fernández-Nieto , José Garres-Díaz , Gladys Narbona-Reina

A mathematical smooth function means that the function has continuous derivatives to a certain degree C(k). We call it a k-smooth function or a smooth function if k can grow infinitively. Based on quantum physics, there is no such smooth…

Numerical Analysis · Mathematics 2010-05-21 Li Chen

We propose a new class of finite element approximations to ideal compressible magnetohydrodynamic equations in smooth regime. Following variational approximations developed for fluid models in the last decade, our discretizations are built…

Numerical Analysis · Mathematics 2024-02-29 Valentin Carlier , Martin Campos-Pinto

In this paper we introduce discrete gradient methods to discretize irreversible port-Hamiltonian systems showing that the main qualitative properties of the continuous system are preserved using this kind discretizations methods.

Numerical Analysis · Mathematics 2023-03-15 Alexandre Anahory Simoes , David Martín de Diego , Bernhard Maschke

We give an introduction to discrete functional analysis techniques for stationary and transient diffusion equations. We show how these techniques are used to establish the convergence of various numerical schemes without assuming…

Numerical Analysis · Mathematics 2016-02-25 Jerome Droniou

This paper aims to develop and analyze a numerical scheme for solving the backward problem of semilinear subdiffusion equations. We establish the existence, uniqueness, and conditional stability of the solution to the inverse problem by…

Numerical Analysis · Mathematics 2025-05-07 Xu Wu , Jiang Yang , Zhi Zhou

Discrete numerical methods with finite time-steps represent a practical technique to solve initial-value problems involving nonlinear differential equations. These methods seem particularly useful to the study of chaos since no analytical…

Dynamical Systems · Mathematics 2009-12-31 Lun-Shin Yao

A proof of convergence is given for semi- and full discretizations of mean curvature flow of closed two-dimensional surfaces. The numerical method proposed and studied here combines evolving finite elements, whose nodes determine the…

Numerical Analysis · Mathematics 2019-06-27 Balázs Kovács , Buyang Li , Christian Lubich

The article proposes formulating and codifying a set of applied numerical methods, coined as Deep Learning Discrete Calculus (DLDC), that uses the knowledge from discrete numerical methods to interpret the deep learning algorithms through…

Numerical Analysis · Mathematics 2022-12-01 Sourav Saha , Chanwook Park , Stefan Knapik , Jiachen Guo , Owen Huang , Wing Kam Liu

This paper explores the critical role of differentiation approaches for data-driven differential equation discovery. Accurate derivatives of the input data are essential for reliable algorithmic operation, particularly in real-world…

Machine Learning · Computer Science 2023-11-13 Mikhail Masliaev , Ilya Markov , Alexander Hvatov

The goal of this paper is to study approaches to bridge the gap between first-order and second-order type methods for composite convex programs. Our key observations are: i) Many well-known operator splitting methods, such as…

Optimization and Control · Mathematics 2016-09-27 Xiantao Xiao , Yongfeng Li , Zaiwen Wen , Liwei Zhang

Traditional problems in computational geometry involve aspects that are both discrete and continuous. One such example is nearest-neighbor searching, where the input is discrete, but the result depends on distances, which vary continuously.…

Computational Geometry · Computer Science 2023-08-21 Ahmed Abdelkader , David M. Mount

Taylor's formula holds significant importance in function representation, such as solving differential difference equations, ordinary differential equations, partial differential equations, and further promotes applications in visual…

Machine Learning · Computer Science 2025-07-15 Guoyou Wang , Yihua Tan , Shiqi Liu