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Related papers: On stable numerical differentiation

200 papers

We study regularity and numerical methods for two-sided fractional diffusion equations with a lower-order term. We show that the regularity of the solution in weighted Sobolev spaces can be greatly improved compared to that in standard…

Numerical Analysis · Mathematics 2017-05-23 Zhaopeng Hao , Guang Lin , Zhongqiang Zhang

In this work we study the problem of step size selection for numerical schemes, which guarantees that the numerical solution presents the same qualitative behavior as the original system of ordinary differential equations, by means of tools…

Numerical Analysis · Mathematics 2015-05-13 Iasson Karafyllis , Lars Grune

Equations arising in General Relativity are usually too complicated to be solved analytically and one has to rely on numerical methods to solve sets of coupled partial differential equations. Among the possible choices, this paper focuses…

General Relativity and Quantum Cosmology · Physics 2016-06-22 Philippe Grandclement , Jérôme Novak

In this paper we explain how to convert discrete invariants into stable ones via what we call hierarchical stabilization. We illustrate this process by constructing stable invariants for multi-parameter persistence modules with respect to…

Algebraic Topology · Mathematics 2021-04-15 Oliver Gäfvert , Wojciech Chachólski

Integro-partial differential equations occur in many contexts in mathematical physics. Typical examples include time-dependent diffusion equations containing a parameter (e.g., the temperature) that depends on integrals of the unknown…

Analysis of PDEs · Mathematics 2007-05-23 Peter A. Becker

In this paper we propose new sufficient conditions for stability of solutions of systems of Volterra linear integral equations and systems of linear integro-differential Volterra equations. Solution stability conditions for systems of…

Numerical Analysis · Mathematics 2023-04-25 Ilya Boykov , Vladimir Roudnev , Alla Boykova

We discuss a numerical algorithm for solving nonlinear integro-differential equations, and illustrate our findings for the particular case of Volterra type equations. The algorithm combines a perturbation approach meant to render a…

Computational Physics · Physics 2008-11-26 Bogdan Mihaila , Ruth E. Shaw

In this paper, we propose a tensor type of discretization and optimization process for solving high dimensional partial differential equations. First, we design the tensor type of trial function for the high dimensional partial differential…

Numerical Analysis · Mathematics 2022-12-01 Yangfei Liao , Yifan Wang , Hehu Xie

We investigate numerical differentiation formulas on irregular centers in two or more variables that are exact for polynomials of a given order and minimize an absolute seminorm of the weight vector. Error bounds are given in terms of a…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov , Robert Schaback

This paper deals with the use of numerical methods based on random root sampling techniques to solve some theoretical problems arising in the analysis of polynomials. These methods are proved to be practical and give solutions where…

Numerical Analysis · Mathematics 2025-04-15 Yousra Gati , Vladimir Petrov Kostov , Mohamed Chaouki Tarchi

We discuss two numerical methods, based on a path integral approach described in a previous paper (I), for solving the stochastic equations underlying the financial markets: the Monte Carlo approach, and the Green function deterministic…

Statistical Mechanics · Physics 2008-12-10 Marco Rosa-Clot , Stefano Taddei

We develop a hybrid spatial discretization for the wave equation in second order form, based on high-order accurate finite difference methods and discontinuous Galerkin methods. The hybridization combines computational efficiency of finite…

Numerical Analysis · Mathematics 2022-10-26 Siyang Wang , Gunilla Kreiss

The paper studies numerical methods that preserve a Lyapunov function of a dynamical system, i.e. numerical approximations whose energy decreases, just like in the original differential equation. With this aim, a discrete gradient method is…

Numerical Analysis · Mathematics 2022-04-26 Yadira Hernández-Solano , Miguel Atencia

We develop a framework for estimating unknown partial differential equations from noisy data, using a deep learning approach. Given noisy samples of a solution to an unknown PDE, our method interpolates the samples using a neural network,…

Machine Learning · Computer Science 2019-10-24 Ali Hasan , João M. Pereira , Robert Ravier , Sina Farsiu , Vahid Tarokh

The discrete-time, the quantum, and the continuous calculus of variations have been recently unified and extended. Two approaches are followed in the literature: one dealing with minimization of delta integrals; the other dealing with…

Optimization and Control · Mathematics 2010-05-25 Agnieszka B. Malinowska , Delfim F. M. Torres

We formulate the problem of numerical analytic continuation in a way that lets us draw meaningful conclusions about properties of the spectral function based solely on the input data. Apart from ensuring consistency with the input data…

Other Condensed Matter · Physics 2017-01-11 Olga Goulko , Andrey S. Mishchenko , Lode Pollet , Nikolay Prokof'ev , Boris Svistunov

Computational gas dynamics has become a prominent research field both in astrophysics and cosmology. In the first part of this review we intend to briefly describe several of the numerical methods used in this field, discuss their range of…

Astrophysics · Physics 2007-12-24 A. Hujeirat , B. W. Keil , F. Heitsch

This paper focuses on the study of integro-differential equations with delays, presenting a novel perturbation approach. The primary objective is to introduce the concepts of classical and mild solutions for these equations and establish…

Functional Analysis · Mathematics 2023-05-26 Hamid Bounit , Abderrahim Driouich , Said Hadd

In this article, firstly we develop a method for a type of difference equations, applicable to solve approximately a class of first order ordinary differential equation systems. In a second step, we apply the results obtained to solve a…

Numerical Analysis · Mathematics 2017-12-12 Fabio Botelho

Feedforward neural networks offer a promising approach for solving differential equations. However, the reliability and accuracy of the approximation still represent delicate issues that are not fully resolved in the current literature.…

Neural and Evolutionary Computing · Computer Science 2021-12-01 Toni Schneidereit , Michael Breuß