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We study a class of evolutionary partial differential systems with two components related to second order (in time) non-evolutionary equations of odd order in spatial variable. We develop the formal diagonalisation method in symbolic…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 Vladimir S. Novikov , Jing Ping Wang

The recent significant enrichment of the Order Completion Method for nonlinear Systems of PDEs resulted in the global existence of generalized solutions to a large class of such equations. In this paper we investigate the existence and…

Analysis of PDEs · Mathematics 2007-09-14 Jan Harm van der Walt

Polynomial dynamical systems describing interacting particles in the plane are studied. A method replacing integration of a polynomial multi--particle dynamical system by finding polynomial solutions of a partial differential equations is…

Exactly Solvable and Integrable Systems · Physics 2014-07-08 Maria V. Demina , Nikolai A. Kudryashov

Identifying integrable coupled nonlinear ordinary differential equations (ODEs) of dissipative type and deducing their general solutions are some of the challenging tasks in nonlinear dynamics. In this paper we undertake these problems and…

Exactly Solvable and Integrable Systems · Physics 2010-10-28 R. Gladwin Pradeep , V. K. Chandrasekar , M. Senthilvelan , M. Lakshmanan

We introduce a novel numerical method to integrate partial differential equations representing the Hamiltonian dynamics of field theories. It is a multi-symplectic integrator that locally conserves the stress-energy tensor with an excellent…

Numerical Analysis · Mathematics 2017-02-23 Hugo Ricateau , Leticia F. Cugliandolo

The recent rise of deep learning has led to numerous applications, including solving partial differential equations using Physics-Informed Neural Networks. This approach has proven highly effective in several academic cases. However, their…

Numerical Analysis · Mathematics 2024-10-07 Marien Chenaud , Frédéric Magoulès , José Alves

Solving nonlinear partial differential equations (PDEs) with multiple solutions using neural networks has found widespread applications in various fields such as physics, biology, and engineering. However, classical neural network methods…

Machine Learning · Computer Science 2024-05-24 Wenrui Hao , Xinliang Liu , Yahong Yang

We apply topological methods to obtain global continuation results for harmonic solutions of some periodically perturbed ordinary differential equations on a $k$-dimensional differentiable manifold $M \subseteq \mathbb{R}^m$. We assume that…

Classical Analysis and ODEs · Mathematics 2012-04-02 Alessandro Calamai , Marco Spadini

We present a short review of the evolution of the methodology of the Method of simplest equation for obtaining exact particular solutions of nonlinear partial differential equations (NPDEs) and the recent extension of a version of this…

Exactly Solvable and Integrable Systems · Physics 2019-06-20 Nikolay K. Vitanov

In this paper, we overview the recent progresses on the lifespan estimates of classical solutions of the initial value problems for nonlinear wave equations in one space dimension. There are mainly two directions of the developments on the…

Analysis of PDEs · Mathematics 2024-03-19 Hiroyuki Takamura

Parabolic partial differential equations (PDEs) and backward stochastic differential equations (BSDEs) are key ingredients in a number of models in physics and financial engineering. In particular, parabolic PDEs and BSDEs are fundamental…

Numerical Analysis · Mathematics 2020-11-25 Weinan E , Martin Hutzenthaler , Arnulf Jentzen , Thomas Kruse

Ordinary and partial differential equations (ODEs/PDEs) play a paramount role in analyzing and simulating complex dynamic processes across all corners of science and engineering. In recent years machine learning tools are aspiring to…

Machine Learning · Computer Science 2021-06-11 Sifan Wang , Paris Perdikaris

We propose a new algorithm for solving parabolic partial differential equations (PDEs) and backward stochastic differential equations (BSDEs) in high dimension, by making an analogy between the BSDE and reinforcement learning with the…

Numerical Analysis · Mathematics 2020-07-14 Weinan E , Jiequn Han , Arnulf Jentzen

We review how diffeologies complete the settings classically used from infinite dimensional geometry to partial differential equations, based on classical settings of functional analysis and with classical mapping spaces as key examples. As…

Differential Geometry · Mathematics 2023-02-16 Nico Goldammer , Jean-PIerre Magnot , Kathrin Welker

It is shown that large classes of nonlinear systems of PDEs, with possibly associated initial and/or boundary value problems, can be solved by the method of order completion. The solutions obtained can be assimilated with Hausdorff…

Analysis of PDEs · Mathematics 2007-05-23 Roumen Anguelov , Elemer E Rosinger

Applications in quantitative finance such as optimal trade execution, risk management of options, and optimal asset allocation involve the solution of high dimensional and nonlinear Partial Differential Equations (PDEs). The connection…

Machine Learning · Statistics 2019-10-28 Batuhan Güler , Alexis Laignelet , Panos Parpas

We investigate the integrability of Nonlinear Partial Differential Equations (NPDEs). The concepts are developed by firstly discussing the integrability of the KdV equation. We proceed by generalizing the ideas introduced for the KdV…

solv-int · Physics 2015-06-26 H. J. S. Dorren

We extend a recently developed method to solve semi-linear PDEs to the case of a degenerated diffusion. Being a pure Monte Carlo method it does not suffer from the so called curse of dimensionality and it can be used to solve problems that…

Probability · Mathematics 2018-05-15 Xavier Warin

New technique of integration of certain types of partial differential equations is developed. For this purpose non-commutative integration over Cayley-Dickson algebras is used. Applications to non-linear vector partial differential…

Analysis of PDEs · Mathematics 2018-12-18 S. V. Ludkovsky

Simulations of the dynamics generated by partial differential equations (PDEs) provide approximate, numerical solutions to initial value problems. Such simulations are ubiquitous in scientific computing, but the correctness of the results…

Numerical Analysis · Mathematics 2026-01-09 Jan Bouwe van den Berg , Maxime Breden
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