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In this work, we develop a localized numerical scheme with low regularity requirements for solving time-fractional integro-differential equations. First, a fully discrete numerical scheme is constructed. Specifically, for temporal…

Numerical Analysis · Mathematics 2025-12-02 Lijing Zhao , Rui Zhao , Wenyi Tian , Yufeng Nie

Recently, we have proposed a new diffusive representation for fractional derivatives and, based on this representation, suggested an algorithm for their numerical computation. From the construction of the algorithm, it is immediately…

Numerical Analysis · Mathematics 2022-04-12 Kai Diethelm

A second order accurate, linear numerical method is analyzed for the Landau-Lifshitz equation with large damping parameters. This equation describes the dynamics of magnetization, with a non-convexity constraint of unit length of the…

Numerical Analysis · Mathematics 2021-11-16 Yongyong Cai , Jingrun Chen , Cheng Wang , Changjian Xie

As datasets grow it becomes infeasible to process them completely with a desired model. For giant datasets, we frame the order in which computation is performed as a decision problem. The order is designed so that partial computations are…

Computation · Statistics 2014-03-18 Daniel John Lawson , Niall M Adams

This study concerns numerical methods for efficiently solving the Richards equation where different weak formulations and computational techniques are analyzed. The spatial discretizations are based on standard or mixed finite element…

Numerical Analysis · Mathematics 2021-05-12 Keita Sana , Beljadid Abdelaziz , Bourgault Yves

The Variation Evolving Method (VEM) that originates from the continuous-time dynamics stability theory seeks the optimal solutions with variation evolution principle. After establishing the first and the second evolution equations within…

Systems and Control · Computer Science 2025-01-28 Sheng Zhang , Fei Liao , Kai-Feng He

There is an abundance of empirical evidence in the numerical relativity literature that the form in which the Einstein evolution equations are written plays a significant role in the lifetime of numerical simulations. This paper attempts to…

General Relativity and Quantum Cosmology · Physics 2009-11-10 David R. Fiske

Neural networks have emerged as promising tools for solving partial differential equations (PDEs), particularly through the application of neural operators. Training neural operators typically requires a large amount of training data to…

Machine Learning · Computer Science 2025-01-27 Chaoyu Liu , Chris Budd , Carola-Bibiane Schönlieb

Reducing orbital eccentricity in numerical relativity simulations of binary black holes is essential for producing astrophysically relevant gravitational wave models, as many of these systems are expected to be near-circular in nature.…

General Relativity and Quantum Cosmology · Physics 2026-04-27 Vittoria Tommasini , Nils L. Vu , Mark A. Scheel , Saul A. Teukolsky

Recently, it has been proven that evolutionary algorithms produce good results for a wide range of combinatorial optimization problems. Some of the considered problems are tackled by evolutionary algorithms that use a representation which…

Neural and Evolutionary Computing · Computer Science 2013-01-18 Benjamin Doerr , Anton Eremeev , Frank Neumann , Madeleine Theile , Christian Thyssen

We apply recent results in the theory of PDE, specifically in problems with two different time scales, on Einstein's equations near their Newtonian limit. The results imply a justification to Postnewtonian approximations when initialization…

General Relativity and Quantum Cosmology · Physics 2015-06-25 Mirta S. Iriondo , Enzo O. Leguizamón , Oscar A. Reula

The conformal formulation of the Einstein constraint equations has been studied intensively since the modern version of the conformal method was first pub- lished in the early 1970s. Proofs of existence and uniqueness of solutions were…

General Relativity and Quantum Cosmology · Physics 2018-08-07 James Dilts , Michael Holst , Tamara Kozareva , David Maxwell

While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and their applicability over macroscopic time scales of physical…

Machine Learning · Statistics 2016-09-08 P. S. Koutsourelakis , Elias Bilionis

A reaction-diffusion problem with a Caputo time derivative is considered. An integral discretization scheme on a graded mesh along with a decomposition of the exact solution is proposed. The truncation error estimate of the discretization…

Numerical Analysis · Mathematics 2018-10-19 Zhongdi Cen , Jian Huang , Anbo Le , Aimin Xu

In this paper we introduce adaptive time step control for simulation of evolution of ice sheets. The discretization error in the approximations is estimated using "Milne's device" by comparing the result from two different methods in a…

Computational Physics · Physics 2019-08-30 Gong Cheng , Per Lötstedt , Lina von Sydow

Computational efficiency demands discretised, hierarchically organised, and individually adaptive time-step sizes (known as the block-step scheme) for the time integration of N-body models. However, most existing N-body codes adapt…

Instrumentation and Methods for Astrophysics · Physics 2017-09-20 Walter Dehnen

We consider fully discrete numerical schemes for a downscaling data assimilation algorithm aimed at approximating the velocity field of the 2D Navier-Stokes equations corresponding to given coarse mesh observational measurements. The time…

Numerical Analysis · Mathematics 2018-05-07 Hussain A. Ibdah , Cecilia F. Mondaini , Edriss S. Titi

This work uses a linear relaxation method to develop efficient numerical schemes for the time-fractional Allen-Cahn and Cahn-Hilliard equations. The L1+-CN formula is used to discretize the fractional derivative, and an auxiliary variable…

Numerical Analysis · Mathematics 2025-06-16 Hui Yu , Zhaoyang Wang , Ping Lin

This article studies the solutions of time-dependent differential inclusions which is motivated by their utility in the modeling of certain physical systems. The differential inclusion is described by a time-dependent set-valued mapping…

Optimization and Control · Mathematics 2021-07-05 Kanat Camlibel , Luigi Iannelli , Aneel Tanwani

This work is focused on the application of functional-type a posteriori error estimates and corresponding indicators to a class of time-dependent problems. We consider the algorithmic part of their derivation and implementation and also…

Numerical Analysis · Computer Science 2017-05-25 Bärbel Holm , Svetlana Matculevich
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