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Lie symmetry analysis is one of the powerful tools to analyze nonlinear ordinary differential equations. We review the effectiveness of this method in terms of various symmetries. We present the method of deriving Lie point symmetries,…

Exactly Solvable and Integrable Systems · Physics 2023-07-19 M. Senthilvelan , V. K. Chandrasekar , R. Mohanasubha

A method is presented for finding the Lie point symmetry transformations acting simultaneously on difference equations and lattices, while leaving the solution set of the corresponding difference scheme invariant. The method is applied to…

Mathematical Physics · Physics 2013-07-10 Decio Levi , Sébastien Tremblay , Pavel Winternitz

We present a collection of algorithms which utilize dimensional reduction to perform mesh refinement and study possibly singular solutions of time-dependent partial differential equations. The algorithms are inspired by constructions used…

Numerical Analysis · Mathematics 2007-06-21 Panagiotis Stinis

This work is devoted to find the numerical solutions of several one dimensional second-order ordinary differential equations. In a heuristic way, in such equations the quadratic logistic maps regarded as a local function are inserted within…

Numerical Analysis · Mathematics 2021-12-01 J. L. Domenech-Garret , C. Marin-Ferrer

The ability to differentiate through optimization problems has unlocked numerous applications, from optimization-based layers in machine learning models to complex design problems formulated as bilevel programs. It has been shown that…

Optimization and Control · Mathematics 2024-03-05 Lucas Fuentes Valenzuela , Robin Brown , Marco Pavone

This paper introduces a proof calculus for real-analytic differential-algebraic dynamic logic, enabling correct transformations of differential-algebraic equations. Applications include index reductions from differential-algebraic equations…

Logic in Computer Science · Computer Science 2025-05-27 Jonathan Hellwig , André Platzer

The numerical solution of differential equations using machine learning-based approaches has gained significant popularity. Neural network-based discretization has emerged as a powerful tool for solving differential equations by…

Numerical Analysis · Mathematics 2024-01-23 Wenrui Hao , Qingguo Hong , Xianlin Jin

We prove a result on the convex dependence of solutions of ordinary differential equations on an ordered finite-dimensional real vector space with respect to the initial data.

Classical Analysis and ODEs · Mathematics 2010-08-03 Martin Keller-Ressel , Eberhard Mayerhofer , Alexander G. Smirnov

Many statistical models are algebraic in that they are defined by polynomial constraints or by parameterizations that are polynomial or rational maps. This opens the door for tools from computational algebraic geometry. These tools can be…

Statistics Theory · Mathematics 2007-06-13 Mathias Drton

We introduce generalised finite difference methods for solving fully nonlinear elliptic partial differential equations. Methods are based on piecewise Cartesian meshes augmented by additional points along the boundary. This allows for…

Numerical Analysis · Mathematics 2017-06-26 Brittany D. Froese , Tiago Salvador

The identification of a mathematical dynamics model is a crucial step in the designing process of a controller. However, it is often very difficult to identify the system's governing equations, especially in complex environments that…

Systems and Control · Electrical Eng. & Systems 2024-07-01 Tobias Nagel , Marco F. Huber

In this article we present first an algorithm for calculating the determining equations associated with so-called ``nonclassical method'' of symmetry reductions (a la Bluman and Cole) for systems of partial differentail equations. This…

solv-int · Physics 2008-02-03 Peter A. Clarkson , Elizabeth L. Mansfield

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

Singular equations with rank-deficient Jacobians arise frequently in algebraic computing applications. As shown in case studies in this paper, direct and intuitive modeling of algebraic problems often results in nonisolated singular…

Numerical Analysis · Mathematics 2021-02-19 Zhonggang Zeng

Even for the gradient descent (GD) method applied to neural network training, understanding its optimization dynamics, including convergence rate, iterate trajectories, function value oscillations, and especially its implicit acceleration,…

Machine Learning · Computer Science 2026-05-22 Alexander Tyurin

In this paper we develop a differential Galois theory for algebraic Lie-Vessiot systems in algebraic homogeneous spaces. Lie-Vessiot systems are non autonomous vector fields that are linear combinations with time-dependent coefficients of…

Classical Analysis and ODEs · Mathematics 2009-01-29 David Blázquez-Sanz , Juan José Morales-Ruiz

Linear differential equations and recurrences reveal many properties about their solutions. Therefore, these equations are well-suited for representing solutions and computing with special functions. We identify a large class of existing…

Symbolic Computation · Computer Science 2026-01-14 Louis Gaillard

This paper studies the expressive and computational power of discrete Ordinary Differential Equations (ODEs), a.k.a. (Ordinary) Difference Equations. It presents a new framework using these equations as a central tool for computation and…

Logic in Computer Science · Computer Science 2022-09-27 Olivier Bournez , Arnaud Durand

Using exhaustion method and finite differences a new method to solve system of partial differential equations and is presented. This method allows design algorithm to solve linear and nonlinear systems in irregular domains. Applying this…

Numerical Analysis · Mathematics 2025-04-10 Miriam Sosa-Díaz , Faustino Sanchez-Garduno

Lie group theory states that knowledge of a $m$-parameters solvable group of symmetries of a system of ordinary differential equations allows to reduce by $m$ the number of equations. We apply this principle by finding some \emph{affine…

Symbolic Computation · Computer Science 2007-06-13 Alexandre Sedoglavic
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