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One way of constructing explicit expressions of solutions of integrable systems of Partial Differential Equations (PDEs) goes via the Darboux method. This requires the construction of Darboux matrices. Here we introduce a novel algorithm to…

Exactly Solvable and Integrable Systems · Physics 2014-12-01 Antonio Degasperis

An efficient finite-difference time-domain (FDTD) algorithm is built to solve the transverse electric 2D Maxwell's equations with inhomogeneous dielectric media where the electric fields are discontinuous across the dielectric interface.…

Computational Physics · Physics 2023-07-14 Timothy Meagher , Bin Jiang , Peng Jiang

In this paper, an innovative Physical Model-driven Neural Network (PMNN) method is proposed to solve time-fractional differential equations. It establishes a temporal iteration scheme based on physical model-driven neural networks which…

Machine Learning · Computer Science 2023-10-10 Zhiying Ma , Jie Hou , Wenhao Zhu , Yaxin Peng , Ying Li

A discrete Boltzmann model (DBM) is proposed to probe the Rayleigh-Taylor instability (RTI) in two-component compressible flows. Each species has a flexible specific heat ratio and is described by one discrete Boltzmann equation (DBE).…

Soft Condensed Matter · Physics 2017-11-22 Chuandong Lin , Aiguo Xu , Guangcai Zhang , Kaihong Luo , Yingjun Li

An iterative scheme for the Dynamical Systems Method (DSM) is given such that one does not have to solve the Cauchy problem occuring in the application of the DSM for solving ill-conditioned linear algebraic systems. The novelty of the…

Numerical Analysis · Mathematics 2008-03-25 N. S. Hoang , A. G. Ramm

An iterative method is derived for image reconstruction. Among other attributes, this method allows constraints unrelated to the radiation measurements to be incorporated into the reconstructed image. A comparison is made with the widely…

Computational Physics · Physics 2011-01-06 Clinton DeW. Van Siclen

The random feature method (RFM) has demonstrated great potential in bridging traditional numerical methods and machine learning techniques for solving partial differential equations (PDEs). It retains the advantages of mesh-free approaches…

Numerical Analysis · Mathematics 2025-05-02 Mikhail Kuvakin , Zijian Mei , Jingrun Chen

We present a unified framework for solving partial differential equations (PDEs) using video-inpainting diffusion transformer models. Unlike existing methods that devise specialized strategies for either forward or inverse problems under…

Machine Learning · Computer Science 2025-06-18 Edward Li , Zichen Wang , Jiahe Huang , Jeong Joon Park

The multiscale complexity of modern problems in computational science and engineering can prohibit the use of traditional numerical methods in multi-dimensional simulations. Therefore, novel algorithms are required in these situations to…

Numerical Analysis · Mathematics 2021-06-15 Cale Harnish , Luke Dalessandro , Karel Matous , Daniel Livescu

Traveling wave solutions of (2 + 1)-dimensional Zoomeron equation(ZE) are developed in terms of exponential functions involving free parameters. It is shown that the novel Lie group of transformations method is a competent and prominent…

Analysis of PDEs · Mathematics 2017-01-24 Vishakha Jadaun , Sachin Kumar , Yogeeta Garg

A method is presented for finding the Lie point symmetry transformations acting simultaneously on difference equations and lattices, while leaving the solution set of the corresponding difference scheme invariant. The method is applied to…

Mathematical Physics · Physics 2013-07-10 Decio Levi , Sébastien Tremblay , Pavel Winternitz

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

In this work, we illustrate and explore the use of Taylor series as solutions of differential equations. For a large a number of classes of differential equations in the literature, there are plenty of sources where the well known Taylor…

Mathematical Physics · Physics 2025-08-06 Alberto Contreras-Cristan , Jose Gonzalez-Barrios , Raul Rueda

A new way to prove the one-dimensional Cauchy problem's weakly discontinuous solutions for hyperbolic PDEs are on the characteristics is discussed in this paper. To do so, I use wavelet singularity detection methods or WTMM [1] based on…

Analysis of PDEs · Mathematics 2013-12-30 Shijie Gu

Wavelets are a powerful new mathematical tool which offers the possibility to treat in a natural way quantities characterized by several length scales. In this article we will show how wavelets can be used to solve partial differential…

Computational Physics · Physics 2016-09-08 Stefan Goedecker , Oleg Ivanov

Recent work has introduced a simple numerical method for solving partial differential equations (PDEs) with deep neural networks (DNNs). This paper reviews and extends the method while applying it to analyze one of the most fundamental…

Machine Learning · Computer Science 2019-05-14 Craig Michoski , Milos Milosavljevic , Todd Oliver , David Hatch

We use the Unified Transform Method (UTM) for the vector case to resolve an interface problem for the Dirac equation on two semi-infinite domains and two finite domains in the massless and massive cases, respectively. The UTM for the vector…

Analysis of PDEs · Mathematics 2026-05-05 C. A. García-Bibiano

Reaction-Diffusion (RD) systems provide a computational framework that governs many pattern formation processes in nature. Current RD system design practices boil down to trial-and-error parameter search. We propose a differentiable…

Neural and Evolutionary Computing · Computer Science 2021-07-15 Alexander Mordvintsev , Ettore Randazzo , Eyvind Niklasson

We present a novel method for using Neural Networks (NNs) for finding solutions to a class of Partial Differential Equations (PDEs). Our method builds on recent advances in Neural Radiance Field research (NeRFs) and allows for a NN to…

Machine Learning · Computer Science 2022-05-31 Jaroslaw Rzepecki , Daniel Bates , Chris Doran

This paper is concerned with an alternative analytical solution of time-fractional nonlinear Schrodinger equation and nonlinear coupled Schrodinger equation obtained by employing fractional reduced differential transform method. The…

Numerical Analysis · Mathematics 2016-11-23 Brajesh Kumar Singh , Pramod Kumar