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We study the periodical solutions of a Poisson-gradient PDEs system with bounded nonlinearity. Section 1 introduces the basic spaces and functionals. Section 2 studies the weak differential of a function and establishes an inequality.…

Dynamical Systems · Mathematics 2007-05-23 Constantin Udriste , Iulian Duca

We construct all (2+1)-dimensional PDEs depending only on 2nd-order derivatives of unknown which have the Euler-Lagrange form and determine the corresponding Lagrangians. We convert these equations and their Lagrangians to two-component…

Exactly Solvable and Integrable Systems · Physics 2022-05-18 M. B. Sheftel , D. Yazıcı

Learning and solving governing equations of a physical system, represented by partial differential equations (PDEs), from data is a central challenge in a variety of areas of science and engineering. Traditional numerical methods for…

Machine Learning · Computer Science 2024-06-10 Anran Jiao , Haiyang He , Rishikesh Ranade , Jay Pathak , Lu Lu

We consider parabolic PDEs associated with fractional type operators drifted by non-linear singular first order terms. When the drift enjoys some boundedness properties in appropriate Lebesgue and Besov spaces, we establish by exploiting a…

Analysis of PDEs · Mathematics 2022-06-16 Diego Chamorro , Stéphane Menozzi

We describe a way of solving a partial differential equation using the differential invariants of its point symmetries. By first solving its quotient PDE, which is given by the differential syzygies in the algebra of differential…

Differential Geometry · Mathematics 2020-05-15 Eivind Schneider

We propose and implement an algorithm for solving an overdetermined system of partial differential equations in one unknown. Our approach relies on Bour-Mayer method to determine compatibility conditions via Jacobi-Mayer brackets. We solve…

Symbolic Computation · Computer Science 2017-03-07 Célestin Wafo Soh

This paper deals with the solution of large classes of systems of nonlinear partial differential equations (PDEs) in spaces of generalized functions that are constructed as the completion of uniform convergence spaces. The existence result…

Analysis of PDEs · Mathematics 2009-02-18 Jan Harm van der Walt

We propose a finite-dimensional control-based method to approximate solution operators for evolutional partial differential equations (PDEs), particularly in high-dimensions. By employing a general reduced-order model, such as a deep neural…

Numerical Analysis · Mathematics 2024-01-22 Nathan Gaby , Xiaojing Ye

We study a class of partial differential equations (PDEs) in the family of the so-called Euler-Poincar\'e differential systems, with the aim of developing a foundation for numerical algorithms of their solutions. This requires particular…

Numerical Analysis · Mathematics 2015-07-14 Roberto Camassa , Dongyang Kuang , Long Lee

We are interested in the numerical solution of coupled nonlinear partial differential equations (PDEs) in two and three dimensions. Under certain assumptions on the domain, we take advantage of the Kronecker structure arising in standard…

Numerical Analysis · Mathematics 2021-07-21 Gerhard Kirsten

Linear partial differential equations (PDEs) are an important, widely applied class of mechanistic models, describing physical processes such as heat transfer, electromagnetism, and wave propagation. In practice, specialized numerical…

Machine Learning · Computer Science 2024-04-30 Marvin Pförtner , Ingo Steinwart , Philipp Hennig , Jonathan Wenger

We determine a considerable class of nonlinear partial differential equation systems which have global regular solutions. Uniqueness is not a direct general consequence of this method. The scheme can be applied to the incompressible Navier…

Analysis of PDEs · Mathematics 2015-06-02 Joerg Kampen

We formulate probabilistic numerical approximations to solutions of ordinary differential equations (ODEs) as problems in Gaussian process (GP) regression with non-linear measurement functions. This is achieved by defining the measurement…

Methodology · Statistics 2019-04-25 Filip Tronarp , Hans Kersting , Simo Särkkä , Philipp Hennig

Solving partial differential equations (PDEs) is the canonical approach for understanding the behavior of physical systems. However, large scale solutions of PDEs using state of the art discretization techniques remains an expensive…

Computational Engineering, Finance, and Science · Computer Science 2021-01-14 Xiaoxuan Zhang , Krishna Garikipati

The development of functions of real variables in Taylor and Frobenius series (whole series which are formed in nonorthogonal, nonperiodic bases), in sinusoidal Fourier series (bases of orthogonal, periodic functions), in series of special…

Functional Analysis · Mathematics 2020-08-03 Arpad Török , Stoian Petrescu , Michel Feidt

We propose a Bernoulli-barycentric rational matrix collocation method for two-dimensional evolutionary partial differential equations (PDEs) with variable coefficients that combines Bernoulli polynomials with barycentric rational…

Numerical Analysis · Mathematics 2024-02-13 Wei-Hua Luo , Xian-Ming Gu , Bruno Carpentieri , Jun Guo

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

We are concerned with the arithmetic of solutions to ordinary or partial nonlinear differential equations which are algebraic in the indeterminates and their derivatives. We call these solutions D-algebraic functions, and their equations…

Symbolic Computation · Computer Science 2024-06-18 Bertrand Teguia Tabuguia

Selfdual variational calculus is further refined and used to address questions of existence of local and global solutions for various parabolic semi-linear equations, Hamiltonian systems of PDEs, as well as certain nonlinear Schrodinger…

Analysis of PDEs · Mathematics 2007-06-07 Nassif Ghoussoub , Abbas Moameni

In this work we present a data-driven method for the discovery of parametric partial differential equations (PDEs), thus allowing one to disambiguate between the underlying evolution equations and their parametric dependencies. Group…

Numerical Analysis · Mathematics 2018-06-05 Samuel Rudy , Alessandro Alla , Steven L. Brunton , J. Nathan Kutz