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In this paper, we develop a new discontinuous Galerkin method for solving several types of partial differential equations (PDEs) with high order spatial derivatives. We combine the advantages of local discontinuous Galerkin (LDG) method and…

Numerical Analysis · Mathematics 2020-03-13 Qi Tao , Yan Xu , Chi-Wang Shu

We provide the details of an implementation of Fourier techniques for solving second-order linear partial differential equations (with constant coefficients) using a computer algebra system. The general Sturm-Liouville problem for the heat,…

Numerical Analysis · Mathematics 2026-04-28 Emmanuel Roque , José A Vallejo

The study gives a brief overview of existing modifications of the method of functional separation of variables for nonlinear PDEs. It proposes a more general approach to the construction of exact solutions to nonlinear equations of applied…

Mathematical Physics · Physics 2020-01-07 Andrei D. Polyanin

Realistic physical phenomena exhibit random fluctuations across many scales in the input and output processes. Models of these phenomena require stochastic PDEs. For three-dimensional coupled (vector-valued) stochastic PDEs (SPDEs), for…

Computational Engineering, Finance, and Science · Computer Science 2022-08-24 Ajit Desai , Mohammad Khalil , Chris L. Pettit , Dominique Poirel , Abhijit Sarkar

In his monograph Chebyshev and Fourier Spectral Methods, John Boyd claimed that, regarding Fourier spectral methods for solving differential equations, ``[t]he virtues of the Fast Fourier Transform will continue to improve as the relentless…

Numerical Analysis · Mathematics 2023-02-03 Craig Gross , Mark Iwen

In this article, we have developed a higher order compact numerical method for variable coefficient parabolic problems with mixed derivatives. The finite difference scheme, presented here for two-dimensional domains, is based on fourth…

Numerical Analysis · Mathematics 2013-12-19 Shuvam Sen

Spectral and spectral element methods using Galerkin type formulations are efficient for solving linear fractional PDEs (FPDEs) of constant order but are not efficient in solving nonlinear FPDEs and cannot handle FPDEs with variable-order.…

Numerical Analysis · Mathematics 2019-03-27 Tinggang Zhao , Zhiping Mao , George Em Karniadakis

Derivative boundary conditions introduce challenges for mesh-free discretizations of PDEs on surfaces, especially when the domain is represented by randomly sampled point clouds. The recently developed two-step tangent-space RBF-generated…

Numerical Analysis · Mathematics 2026-03-31 Peng Chen , Shixiao Willing Jiang , Rongji Li , Qile Yan

We present a discretization-free scalable framework for solving a large class of mass-conserving partial differential equations (PDEs), including the time-dependent Fokker-Planck equation and the Wasserstein gradient flow. The main…

Machine Learning · Computer Science 2023-11-15 Lingxiao Li , Samuel Hurault , Justin Solomon

Multiscale and multiphysics problems need novel numerical methods in order for them to be solved correctly and predictively. To that end, we develop a wavelet based technique to solve a coupled system of nonlinear partial differential…

Numerical Analysis · Mathematics 2023-03-22 Cale Harnish , Luke Dalessandro , Karel Matous , Daniel Livescu

Fractional differential equations (FDEs) are an extension of the theory of fractional calculus. However, due to the difficulty in finding analytical solutions, there have not been extensive applications of FDEs until recent decades. With…

Numerical Analysis · Mathematics 2020-07-20 Nirupama Bhattacharya , Gabriel A. Silva

Anomalous diffusion is a phenomenon that cannot be modeled accurately by second-order diffusion equations, but is better described by fractional diffusion models. The nonlocal nature of the fractional diffusion operators makes substantially…

Numerical Analysis · Mathematics 2018-03-08 K. Mustapha , K. Furati , O. M. Knio , O. Le Maitre

This paper is concerned with moving mesh finite difference solution of partial differential equations. It is known that mesh movement introduces an extra convection term and its numerical treatment has a significant impact on the stability…

Numerical Analysis · Mathematics 2015-07-31 Weizhang Huang

We present a high-order radial basis function finite difference (RBF-FD) framework for the solution of advection-diffusion equations on time-varying domains. Our framework is based on a generalization of the recently developed Overlapped…

Numerical Analysis · Mathematics 2021-09-15 Varun Shankar , Grady B. Wright , Aaron L. Fogelson

We present DeepFDM, a differentiable finite-difference framework for learning spatially varying coefficients in time-dependent partial differential equations (PDEs). By embedding a classical forward-Euler discretization into a convolutional…

Numerical Analysis · Mathematics 2025-07-30 Patrick Chatain , Michael Rizvi-Martel , Guillaume Rabusseau , Adam Oberman

Partial differential equations are frequently solved using a global basis, such as the Fourier series, due to excellent convergence. However, convergence becomes impaired when discontinuities are present due to the Gibbs phenomenon,…

Computational Physics · Physics 2021-03-17 Parry Y Chen , Yonatan Sivan

In this paper, we present how high-order accurate solutions to elliptic partial differential equations can be achieved in arbitrary spatial domains using radial basis function-generated finite differences (RBF-FD) on unfitted node sets…

Numerical Analysis · Mathematics 2024-07-23 Morten E. Nielsen , Bengt Fornberg

Convection-diffusion equations arise in a variety of applications such as particle transport, electromagnetics, and magnetohydrodynamics. Simulation of the convection-dominated regime for these problems, even with high-fidelity techniques,…

Numerical Analysis · Mathematics 2023-05-24 James H. Adler , Casey Cavanaugh , Xiaozhe Hu , Andy Huang , Nathaniel Trask

The present work proposes a well-balanced finite volume-type numerical method for the solution of non-conservative hyperbolic partial differential equations (PDEs) with source terms. The method is characterized, first, by the use of a…

Numerical Analysis · Mathematics 2026-05-06 Chiara Colombo , Caterina Dalmaso , Lucas O. Müller , Annunziato Siviglia

Solving partial differential equations is difficult. Recently proposed neural resolution-invariant models, despite their effectiveness and efficiency, usually require equispaced spatial points of data. However, sampling in spatial domain is…

Machine Learning · Computer Science 2023-03-21 Haitao Lin , Lirong Wu , Yongjie Xu , Yufei Huang , Siyuan Li , Guojiang Zhao , Stan Z. Li