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In this short communication we introduce a rather simple autonomous system of 2 nonlinearly-coupled first-order Ordinary Differential Equations (ODEs), whose initial-values problem is explicitly solvable by algebraic operations. Its ODEs…

Dynamical Systems · Mathematics 2023-06-22 Francesco Calogero , Farrin Payandeh

A method for approximating sixth-order ordinary differential equations is proposed, which utilizes a deep learning feedforward artificial neural network, referred to as a neural solver. The efficacy of this unsupervised machine learning…

Numerical Analysis · Mathematics 2025-09-16 Janavi Bhalala , B. Veena S. N. Rao

A probabilistic representation for initial value semilinear parabolic problems based on generalized random trees has been derived. Two different strategies have been proposed, both requiring generating suitable random trees combined with a…

Numerical Analysis · Mathematics 2024-02-13 Juan A. Acebron , Angel Rodriguez-Rozas

We explicate a procedure to solve general linear differential equations, which connects the desired solutions to monomials x^m of an appropriate degree m. In the process the underlying symmetry of the equations under study, as well as that…

Mathematical Physics · Physics 2012-05-03 N. Gurappa , Abhijit Sen , Rajneesh Atre , Prasanta K. Panigrahi

Motivated by a certain molecular reconstruction methodology in cryo-electron microscopy, we consider the problem of solving a linear system with two unknown orthogonal matrices, which is a generalization of the well-known orthogonal…

Optimization and Control · Mathematics 2017-03-07 Teng Zhang , Amit Singer

In this paper, we tackle the parametric complete multiplicity problem for a univariate polynomial. Our approach to the parametric complete multiplicity problem has a significant difference from the classical method, which relies on repeated…

Symbolic Computation · Computer Science 2024-12-31 Simin Qin , Bican Xia , Jing Yang

We generalize the Safe Extremum Seeking algorithm to address the minimization of an unknown objective function subject to multiple unknown inequality and equality constraints, relying on recent results of gradient flow systems. These…

Optimization and Control · Mathematics 2025-10-09 Alan Williams , Jorge Cortés , Alexander Scheinker

We present a new algorithm for computing a truncated Markov basis of a lattice. In general, this new algorithm is faster than existing methods. We then extend this new algorithm so that it solves the linear integer feasibility problem with…

Optimization and Control · Mathematics 2007-05-23 Peter N. Malkin

We propose a new algorithm for computing validated bounds for the solutions to the first order variational equations associated to ODEs. These validated solutions are the kernel of numerics computer-assisted proofs in dynamical systems…

Numerical Analysis · Mathematics 2020-10-15 Irmina Walawska , Daniel Wilczak

We propose a physical analogy between finding the solution of an ordinary differential equation (ODE) and a $N$ particle problem in statistical mechanics. It uses the fact that the solution of an ODE is equivalent to obtain the minimum of a…

Statistical Mechanics · Physics 2009-11-13 M. L. Alemany , M. Febbo , S. A. Vera

The paper concerns the theory of parabolic equations on a broad class of closed subsets of Euclidean space possessing a kind of tangent structure. A necessary framework for considering evolutionary problems is developed, and fundamental…

Analysis of PDEs · Mathematics 2023-11-07 Łukasz Chomienia

We present a graph-theoretical approach that can detect which equations of a delay differential-algebraic equation (DDAE) need to be differentiated or shifted to construct a solution of the DDAE. Our approach exploits the observation that…

Dynamical Systems · Mathematics 2020-10-30 Ines Ahrens , Benjamin Unger

Linear differential equations of arbitrary order with polynomial coefficients are considered. Specifically, necessary and sufficient conditions for the existence of polynomial solutions of a given degree are obtained for these equations. An…

Mathematical Physics · Physics 2011-09-27 H. Azad , A. Laradji , M. T. Mustafa

We introduce Prob-GParareal, a probabilistic extension of the GParareal algorithm designed to provide uncertainty quantification for the Parallel-in-Time (PinT) solution of (ordinary and partial) differential equations (ODEs, PDEs). The…

Computation · Statistics 2025-09-05 Guglielmo Gattiglio , Lyudmila Grigoryeva , Massimiliano Tamborrino

The dynamic algorithm to compute a Gr\"obner basis is nearly twenty years old, yet it seems to have arrived stillborn; aside from two initial publications, there have been no published followups. One reason for this may be that, at first…

Commutative Algebra · Mathematics 2014-02-18 Massimo Caboara , John Perry

In this paper, we propose distributed algorithms that solve a system of Boolean equations over a network, where each node in the network possesses only one Boolean equation from the system. The Boolean equation assigned at any particular…

Optimization and Control · Mathematics 2021-03-04 Hongsheng Qi , Bo Li , Rui-Juan Jing , Lei Wang , Alexandre Proutiere , Guodong Shi

Probabilistic ordinary differential equation (ODE) solvers have been introduced over the past decade as uncertainty-aware numerical integrators. They typically proceed by assuming a functional prior to the ODE solution, which is then…

Numerical Analysis · Mathematics 2025-03-25 Yvann Le Fay , Simo Särkkä , Adrien Corenflos

The present work includes some of the author's original researches on integer solutions of Diophantine liner equations and systems. The notion of "general integer solution" of a Diophantine linear equation with two unknowns is extended to…

General Mathematics · Mathematics 2007-11-28 Florentin Smarandache

The novel contribution of this paper relies in the proposal of a fully implicit numerical method designed for nonlinear degenerate parabolic equations, in its convergence/stability analysis, and in the study of the related computational…

Numerical Analysis · Mathematics 2010-01-20 Matteo Semplice , Marco Donatelli , Stefano Serra-Capizzano

Solving diverse partial differential equations (PDEs) is fundamental in science and engineering. Large language models (LLMs) have demonstrated strong capabilities in code generation, symbolic reasoning, and tool use, but reliably solving…

Machine Learning · Computer Science 2026-04-24 Zhuoyuan Wang , Hanjiang Hu , Xiyu Deng , Saviz Mowlavi , Yorie Nakahira