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We describe a neural-based method for generating exact or approximate solutions to differential equations in the form of mathematical expressions. Unlike other neural methods, our system returns symbolic expressions that can be interpreted…

Machine Learning · Computer Science 2020-11-16 Maysum Panju , Kourosh Parand , Ali Ghodsi

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

A power series being given as the solution of a linear differential equation with appropriate initial conditions, minimization consists in finding a non-trivial linear differential equation of minimal order having this power series as a…

Symbolic Computation · Computer Science 2023-07-19 Alin Bostan , Tanguy Rivoal , Bruno Salvy

We consider algebraic ordinary differential equations (AODEs) and study their polynomial and rational solutions. A sufficient condition for an AODE to have a degree bound for its polynomial solutions is presented. An AODE satisfying this…

Symbolic Computation · Computer Science 2018-04-24 Thieu N. Vo , Yi Zhang

Linear algebraic expressions are the essence of many computationally intensive problems, including scientific simulations and machine learning applications. However, translating high-level formulations of these expressions to efficient…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-03-22 Dániel Berényi , András Leitereg , Gábor Lehel

The analysis of solutions to algebraic equations is further simplified. A couple of functions and their analytic continuation or root findings are required.

General Physics · Physics 2007-05-23 Gordon Chalmers

Consider an algorithm computing in a differential field with several commuting derivations such that the only operations it performs with the elements of the field are arithmetic operations, differentiation, and zero testing. We show that,…

Commutative Algebra · Mathematics 2021-08-31 Wei Li , Alexey Ovchinnikov , Gleb Pogudin , Thomas Scanlon

Differential-elimination algorithms apply a finite number of differentiations and eliminations to systems of partial differential equations. For systems that are polynomially nonlinear with rational number coefficients, they guarantee the…

Symbolic Computation · Computer Science 2024-10-17 Siyuan Deng , Michelle Hatzel , Gregory Reid , Wenqiang Yang , Wenyuan Wu

We deal with the numerical solution of linear partial differential equations (PDEs) with focus on the goal-oriented error estimates including algebraic errors arising by an inaccurate solution of the corresponding algebraic systems. The…

Numerical Analysis · Mathematics 2020-01-08 Vít Dolejší , Petr Tichý

In the theory and practice of inverse problems for partial differential equations (PDEs) much attention is paid to the problem of the identification of coefficients from some additional information. This work deals with the problem of…

Numerical Analysis · Computer Science 2013-04-23 P. N. Vabishchevich , V. I. Vasil'ev

This book encompasses both traditional and modern methods treating partial differential equation (PDE) of first order and second order. There is a balance in making a selfcontained mathematical text and introducing new subjects. The Lie…

Analysis of PDEs · Mathematics 2010-04-14 A. D. R. Choudary , Saima Parveen , Constantin Varsan

Within recent years, considerable progress has been made regarding high-performance solvers for Partial Differential Equations (PDEs), yielding potential gains in efficiency compared to industry standard tools. However, the latter largely…

Numerical Analysis · Mathematics 2024-02-20 Patrick Zimbrod , Michael Fleck , Johannes Schilp

Partial Differential Equations (PDE) are fundamental to model different phenomena in science and engineering mathematically. Solving them is a crucial step towards a precise knowledge of the behaviour of natural and engineered systems. In…

We construct stable periodic solutions for a simple form nonlinear delay differential equation (DDE) with a periodic coefficient. The equation involves one underlying nonlinearity with the multiplicative periodic coefficient. The well-known…

Dynamical Systems · Mathematics 2024-02-14 Anatoli Ivanov , Sergiy Shelyag

We introduce a new diagrammatic notation for representing the result of (algebraic) effectful computations. Our notation explicitly separates the effects produced during a computation from the possible values returned, this way simplifying…

Programming Languages · Computer Science 2020-01-13 Ugo Dal Lago , Francesco Gavazzo

A large family of linear, usually overdetermined, systems of partial differential equations that admit a multiplication of solutions, i.e, a bi-linear and commutative mapping on the solution space, is studied. This family of PDE's contains…

Analysis of PDEs · Mathematics 2008-03-19 Jens Jonasson

In this paper we introduce and investigate a new kind of functional (including ordinary and evolutionary partial) differential equations. The main goal of this paper is to explore our new philosophy by some examples on functional ODEs and…

Analysis of PDEs · Mathematics 2014-02-14 De-Xing Kong , Cheng Zhang

This book is mainly an exposition of the author's works and his joint works with his former students on explicit representations of finite-dimensional simple Lie algebras, related partial differential equations, linear orthogonal algebraic…

Representation Theory · Mathematics 2016-01-29 Xiaoping Xu

A formal definition of the graded algebra $\mathcal{R}$ of modular linear differential operators is given and its properties are studied. An algebraic structure of the solutions to modular linear differential equations (MLDEs) is shown. It…

Number Theory · Mathematics 2018-07-20 Fumitoshi Yamashita

Partial differential equations (PDEs) are among the most universal and parsimonious descriptions of natural physical laws, capturing a rich variety of phenomenology and multi-scale physics in a compact and symbolic representation. This…

Machine Learning · Computer Science 2023-03-31 Steven L. Brunton , J. Nathan Kutz