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In recent work, Li et al.\ (Comm.\ Math.\ Sci., 7:81-107, 2009) developed a diffuse-domain method (DDM) for solving partial differential equations in complex, dynamic geometries with Dirichlet, Neumann, and Robin boundary conditions. The…

Numerical Analysis · Mathematics 2015-05-18 Karl Yngve Lervåg , John Lowengrub

We present a method to solve fractional optimal control problems, where the dynamic depends on integer and Caputo fractional derivatives. Our approach consists to approximate the initial fractional order problem with a new one that involves…

Optimization and Control · Mathematics 2016-10-25 Ricardo Almeida , Delfim F. M. Torres

Fractional differential equations are powerful mathematical descriptors for intricate physical phenomena in a compact form. However, compared to integer ordinary or partial differential equations, solving fractional differential equations…

Analysis of PDEs · Mathematics 2025-06-16 Donya Dabiri , Joshua DaRosa , Milad Saadat , Deepak Mangal , Safa Jamali

Many numerical codes now under development to solve Einstein's equations of general relativity in 3+1 dimensional spacetimes employ the standard ADM form of the field equations. This form involves evolution equations for the raw spatial…

General Relativity and Quantum Cosmology · Physics 2009-10-31 Thomas W. Baumgarte , Stuart L. Shapiro

Finite-difference time-domain (FDTD) is an effective algorithm for resolving Maxwell equations directly in time domain. Although FDTD has obtained sufficient development, there still exists some improvement space for it, such as…

Computational Physics · Physics 2023-03-29 Huicheng Guo , Henglei Du , Chengpu Liu

In this paper the singular Emden-Fowler equation of fractional order is introduced and a computational method is proposed for its numerical solution. For the approximation of the solutions we have used Boubaker polynomials and defined the…

Numerical Analysis · Mathematics 2022-02-28 Abdelkrim Bencheikh , Lakhdar Chiter

In this paper, we introduce the Deep Finite Volume Method (DFVM), an innovative deep learning framework tailored for solving high-order (order \(\geq 2\)) partial differential equations (PDEs). Our approach centers on a novel loss function…

Numerical Analysis · Mathematics 2024-07-15 Jianhuan Cen , Qingsong Zou

Fractional differential equations (FDEs) describe subdiffusion behavior of dynamical systems. Its non-local structure requires taking into account the whole evolution history during the time integration, which then possibly causes…

Numerical Analysis · Mathematics 2022-02-17 Ustim Khristenko , Barbara Wohlmuth

In this article, we propose a two-grid based adaptive proper orthogonal decomposition (POD) method to solve the time dependent partial differential equations. Based on the error obtained in the coarse grid, we propose an error indicator for…

Numerical Analysis · Mathematics 2020-07-24 Xiaoying Dai , Xiong Kuang , Jack Xin , Aihui Zhou

We consider a global variable consensus ADMM algorithm for solving large-scale PDE parameter estimation problems asynchronously and in parallel. To this end, we partition the data and distribute the resulting subproblems among the available…

Numerical Analysis · Mathematics 2019-05-01 Samy Wu Fung , Lars Ruthotto

We are interested in numerically approximating the solution ${\bf U}(t)$ of the large dimensional semilinear matrix differential equation $\dot{\bf U}(t) = { \bf A}{\bf U}(t) + {\bf U}(t){ \bf B} + {\cal F}({\bf U},t)$, with appropriate…

Numerical Analysis · Mathematics 2021-05-26 Gerhard Kirsten , Valeria Simoncini

We introduce the multivariate decomposition finite element method for elliptic PDEs with lognormal diffusion coefficient $a=\exp(Z)$ where $Z$ is a Gaussian random field defined by an infinite series expansion $Z(\boldsymbol{y}) =…

Numerical Analysis · Mathematics 2021-09-28 Dong T. P. Nguyen , Dirk Nuyens

The use of deep learning methods for solving PDEs is a field in full expansion. In particular, Physical Informed Neural Networks, that implement a sampling of the physical domain and use a loss function that penalizes the violation of the…

Machine Learning · Computer Science 2021-12-08 Valentin Mercier , Serge Gratton , Pierre Boudier

We evaluate the performance of novel numerical methods for solving one-dimensional nonlinear fractional dispersive and dissipative evolution equations. The methods are based on affine combinations of time-splitting integrators and…

Numerical Analysis · Mathematics 2023-09-22 Lisandro A. Raviola , Mariano F. De Leo

Dynamic Mode Decomposition (DMD) is a data based modeling tool that identifies a matrix to map a quantity at some time instant to the same quantity in future. We design a new version which we call Adaptive Dynamic Mode Decomposition (ADMD)…

Signal Processing · Electrical Eng. & Systems 2020-12-16 Mohammad N. Murshed , M. Monir Uddin

Semidefinite programs (SDPs) can be solved in polynomial time by interior point methods. However, when the dimension of the problem gets large, interior point methods become impractical in terms of both computational time and memory…

Optimization and Control · Mathematics 2023-11-27 Federico Battista , Marianna De Santis

In this work we study Lie symmetry analysis of initial and boundary value problems for partial differential equations (PDE) with Caputo fractional derivative. We give generalized definition and theorem for the symmetry method for PDE with…

Analysis of PDEs · Mathematics 2020-03-18 Gulistan Iskenderoglu , Dogan Kaya

Computational methods for fractional differential equations exhibit essential instability. Even a minor modification of the coefficients or other entry data may switch good results to the divergent. The goal of this paper is to suggest the…

Numerical Analysis · Mathematics 2021-12-20 P. B. Dubovski , J. A. Slepoi

A finite element scheme for an entirely fractional Allen-Cahn equation with non-smooth initial data is introduced and analyzed. In the proposed nonlocal model, the Caputo fractional in-time derivative and the fractional Laplacian replace…

Numerical Analysis · Mathematics 2020-04-06 Gabriel Acosta , Francisco Bersetche

Nonconvex and structured optimization problems arise in many engineering applications that demand scalable and distributed solution methods. The study of the convergence properties of these methods is in general difficult due to the…

Optimization and Control · Mathematics 2015-05-04 Sindri Magnússon , Pradeep Chathuranga Weeraddana , Michael G. Rabbat , Carlo Fischione
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