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This course, intended for undergraduates familiar with elementary calculus and linear algebra, introduces the extension of differential calculus to functions on more general vector spaces, such as functions that take as input a matrix and…

History and Overview · Mathematics 2025-01-28 Paige Bright , Alan Edelman , Steven G. Johnson

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

An efficient approximate version of implicit Taylor methods for initial-value problems of systems of ordinary differential equations (ODEs) is introduced. The approach, based on an approximate formulation of Taylor methods, produces a…

Numerical Analysis · Mathematics 2024-02-05 Antonio Baeza , Raimund Bürger , María del Carmen Martí , Pep Mulet , David Zorío

We show that the theory of self-adjoint differential equations can be used to provide a satisfactory solution of the inverse variational problem in classical mechanics. A Newtonian equation when transformed to the self-adjoint form allows…

Classical Physics · Physics 2020-10-28 Benoy Talukdar , Supriya Chatterjee , Sekh Golam Ali

This chapter is mainly a tutorial introduction to methods recently developed in order to find all (as opposed to some) meromorphic particular solutions of given nonintegrable, autonomous, algebraic ordinary differential equations of any…

Exactly Solvable and Integrable Systems · Physics 2018-06-11 Robert Conte , Tuen Wai Ng , Chengfa Wu

This article proposes modifications of the Parareal algorithm for its application to higher index differential algebraic equations (DAEs). It is based on the idea of applying the algorithm to only the differential components of the equation…

Numerical Analysis · Mathematics 2022-10-05 Idoia Cortes Garcia , Iryna Kulchytska-Ruchka , Sebastian Schöps

A subroutine for very-high-precision numerical solution of a class of ordinary differential equations is provided. For given evaluation point and equation parameters the memory requirement scales linearly with precision $P$, and the number…

Mathematical Physics · Physics 2015-06-05 Amna Noreen , Kåre Olaussen

We have been working in many aspects of the problem of analyzing, understanding and solving ordinary differential equations (first and second order). As we have extensively mentioned, while working in the Darboux type methods, the most…

Mathematical Physics · Physics 2011-04-27 L. G. S. Duarte , L. A. C. P. da Mota

This article is the third in a series the aim of which is to use Lie group theory to obtain exact analytic solutions of Delay Ordinary Differential Systems (DODSs). Such a system consists of two equations involving one independent variable…

Classical Analysis and ODEs · Mathematics 2020-07-09 Vladimir A. Dorodnitsyn , Roman Kozlov , Sergey V. Meleshko , Pavel Winternitz

Differential-algebraic equations (DAEs) are widely used for modeling of dynamical systems. The difficulty in solving numerically a DAE is measured by its differentiation index. For highly accurate simulation of dynamical systems, it is…

Optimization and Control · Mathematics 2019-06-24 Satoru Iwata , Taihei Oki , Mizuyo Takamatsu

Discrete gradient methods are a powerful tool for the time discretization of dynamical systems, since they are structure-preserving regardless of the form of the total energy. In this work, we discuss the application of discrete gradient…

Numerical Analysis · Mathematics 2026-01-06 Philipp L. Kinon , Riccardo Morandin , Philipp Schulze

We propose a machine learning framework to accelerate numerical computations of time-dependent ODEs and PDEs. Our method is based on recasting (generalizations of) existing numerical methods as artificial neural networks, with a set of…

Numerical Analysis · Mathematics 2019-03-08 Siddhartha Mishra

Partial Differential Equations (PDEs) are central to science and engineering. Since solving them is computationally expensive, a lot of effort has been put into approximating their solution operator via both traditional and recently…

Machine Learning · Computer Science 2025-02-14 Alessandro Longhi , Danny Lathouwers , Zoltán Perkó

Computer simulations of differential equations require a time discretization, which inhibits to identify the exact solution with certainty. Probabilistic simulations take this into account via uncertainty quantification. The construction of…

Numerical Analysis · Mathematics 2020-10-15 Philipp Frank , Torsten A. Enßlin

Given a first-order autonomous algebraic ordinary differential equation, we present a method for computing formal power series solutions by means of places. We provide an algorithm for computing a full characterization of possible initial…

Symbolic Computation · Computer Science 2018-11-15 Sebastian Falkensteiner , J. Rafael Sendra

Dual decomposition is a powerful technique for deriving decomposition schemes for convex optimization problems with separable structure. Although the Augmented Lagrangian is computationally more stable than the ordinary Lagrangian, the…

Optimization and Control · Mathematics 2013-02-14 Ion Necoara , Johan A. K. Suykens

We develop an arithmetic analogue of linear partial differential equations in two independent ``space-time'' variables. The spatial derivative is a Fermat quotient operator, while the time derivative is the usual derivation. This allows us…

Analysis of PDEs · Mathematics 2007-05-23 Alexandru Buium , Santiago R. Simanca

The issue of inheriting periodicity of an exact solution of a dynamic system by a difference scheme is considered. It is shown that some difference schemes (midpoint scheme, Kahan scheme) in some special cases provide approximate solutions…

Classical Analysis and ODEs · Mathematics 2024-12-03 Wang Shiwei , Alexander Zorin , Marina Konyaeva , Mikhail Malykh , Leonid Sevastianov

This paper concerns the numerical procedure for solving hybrid optimal control problems with sliding modes. The proposed procedure has several features which distinguishes it from the other procedures for the problem. First of all a sliding…

Optimization and Control · Mathematics 2021-01-18 Radoslaw Pytlak , Damian Suski

In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evaluate the derivative of a function specified by a computer program. AD exploits the fact that every computer program, no matter how…

Mathematical Software · Computer Science 2021-02-03 Vassil Vassilev , Aleksandr Efremov , Oksana Shadura