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Sufficient conditions for either existence or non-existence of traveling wave solutions for a general quasi-linear reaction-diffusion-convection equation, possibly highly degenerate or singular, with discontinuous coefficients are…

Analysis of PDEs · Mathematics 2025-07-09 Umberto Guarnotta , Cristina Marcelli

To approximate solutions of complex nonlinear partial differential equations remains a computational challenge, especially for sets of equations relevant in industry, such as Euler or Navier-Stokes equations. Even the most sophisticated…

Quantum Physics · Physics 2026-03-25 Maximilian Mandelt Buxadé , Stefan Langer , Philipp Bekemeyer

Nonlinear systems of partial differential equations (PDEs) may permit several distinct solutions. The typical current approach to finding distinct solutions is to start Newton's method with many different initial guesses, hoping to find…

Numerical Analysis · Mathematics 2015-07-03 Patrick E. Farrell , Ásgeir Birkisson , Simon W. Funke

We propose a high-order spacetime wavelet method for the solution of nonlinear partial differential equations with a user-prescribed accuracy. The technique utilizes wavelet theory with a priori error estimates to discretize the problem in…

Numerical Analysis · Mathematics 2025-01-14 Cody D. Cochran , Karel Matous

A number of important results of studying large deformations of hyper-elastic shells are obtained using discrete methods of mathematical physics. In the present paper, using the variational method for solving nonlinear boundary problems of…

Analysis of PDEs · Mathematics 2015-06-26 V. A. Trotsenko

A numerical method is proposed for computing time-periodic and relative time-periodic solutions in dissipative wave systems. In such solutions, the temporal period, and possibly other additional internal parameters such as the propagation…

Pattern Formation and Solitons · Physics 2014-08-28 Jianke Yang

In this paper, we investigate a new extragradient algorithm for solving pseudomonotone equilibrium problems on Hadamard manifolds. The algorithm uses a variable stepsize which is updated at each iteration and based on some previous…

Optimization and Control · Mathematics 2021-07-27 Jingjing Fan , Bing Tan , Songxiao Li

This paper discusses the algorithms and implementations of three Mathematica packages for the study of integrability and the computation of closed-form solutions of nonlinear polynomial PDEs. The first package, PainleveTest.m, symbolically…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 Douglas Baldwin , Willy Hereman , Jack Sayers

Using the method of sub-super-solution, we construct a solution of $(-\Delta)^su-cu_z-f(u)=0$ on $\R^3$ of pyramidal shape. Here $(-\Delta)^s$ is the fractional Laplacian of sub-critical order $1/2<s<1$ and $f$ is a bistable nonlinearity.…

Analysis of PDEs · Mathematics 2016-04-07 Hardy Chan , Juncheng Wei

I describe a new algorithm for solving nonlinear wave equations. In this approach, evolution takes place on characteristic hypersurfaces. The algorithm is directly applicable to electromagnetic, Yang-Mills and gravitational fields and other…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Jeffrey Winicour

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

We construct quantum algorithms to compute physical observables of nonlinear PDEs with M initial data. Based on an exact mapping between nonlinear and linear PDEs using the level set method, these new quantum algorithms for nonlinear…

Quantum Physics · Physics 2025-04-22 Shi Jin , Nana Liu

The numerical solution of differential equations can be formulated as an inference problem to which formal statistical approaches can be applied. However, nonlinear partial differential equations (PDEs) pose substantial challenges from an…

Numerical Analysis · Mathematics 2021-08-26 Junyang Wang , Jon Cockayne , Oksana Chkrebtii , T. J. Sullivan , Chris. J. Oates

The construction of stochastic solutions for nonlinear partial differential equations is a powerful method to obtain new exact results and to develop efficient numerical algorithms, in particular when domain decomposition techniques are…

Mathematical Physics · Physics 2012-09-17 Rui Vilela Mendes

We describe a quantum algorithm for preparing states that encode solutions of non-homogeneous linear partial differential equations. The algorithm is a continuous-variable version of matrix inversion: it efficiently inverts differential…

Quantum Physics · Physics 2019-09-11 Juan Miguel Arrazola , Timjan Kalajdzievski , Christian Weedbrook , Seth Lloyd

We introduce DDE-Solver, a Maple package designed for solving Discrete Differential Equations (DDEs). These equations are functional equations relating algebraically a formal power series F(t, u) with polynomial coefficients in a…

Combinatorics · Mathematics 2025-09-11 Hadrien Notarantonio

In this paper we introduce a numerical method for nonlinear parabolic PDEs that combines operator splitting with deep learning. It divides the PDE approximation problem into a sequence of separate learning problems. Since the computational…

Numerical Analysis · Mathematics 2021-10-12 Christian Beck , Sebastian Becker , Patrick Cheridito , Arnulf Jentzen , Ariel Neufeld

The paper develops the method for construction of families of particular solutions to some classes of nonlinear Partial Differential Equations (PDE). Method is based on the specific link between algebraic matrix equations and PDE.…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 A. I. Zenchuk

In the following paper we will consider Navier-Stokes problem and it's interpretation by hyperbolic waves, focusing on wave propagation. We will begin with solution for linear waves, then present problem for non-linear waves. Later we will…

Numerical Analysis · Computer Science 2016-01-22 Erik Arakelyan , Aram Serobyan , Narek Jilavyan

Many types of physics-informed neural network models have been proposed in recent years as approaches for learning solutions to differential equations. When a particular task requires solving a differential equation at multiple…

Machine Learning · Computer Science 2021-11-02 Filipe de Avila Belbute-Peres , Yi-fan Chen , Fei Sha
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