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The Darboux process, also known by many other names, played a very important role in some extremely enjoyable joint work that Hans and I did 25 years ago. I revisit a version of this problem in a case when scalars are replaced by matrices,…

Spectral Theory · Mathematics 2008-08-22 F. Alberto Grünbaum

A systematic algorithm for building integrating factors of the form mu(x,y), mu(x,y') or mu(y,y') for second order ODEs is presented. The algorithm can determine the existence and explicit form of the integrating factors themselves without…

Mathematical Physics · Physics 2007-05-23 E. S. Cheb-Terrab , A. D. Roche

In this paper we propose a general algorithmic framework for first-order methods in optimization in a broad sense, including minimization problems, saddle-point problems and variational inequalities. This framework allows to obtain many…

Differential Equations are among the most important Mathematical tools used in creating models in the science, engineering, economics, mathematics, physics, aeronautics, astronomy, dynamics, biology, chemistry, medicine, environmental…

History and Overview · Mathematics 2020-12-15 Byakatonda Denis

Here, Darboux's classical results about transformations with differential substitutions for hyperbolic equations are extended to the case of parabolic equations of the form $L u = \big(D^2_{x} + a(x,y) D_x + b(x,y) D_y + c(x,y)\big)u=0$. We…

Exactly Solvable and Integrable Systems · Physics 2008-12-17 S. P. Tsarev , E. Shemyakova

In this work, we concern with the high order numerical methods for coupled forward-backward stochastic differential equations (FBSDEs). Based on the FBSDEs theory, we derive two reference ordinary differential equations (ODEs) from the…

Numerical Analysis · Mathematics 2014-03-27 Weidong Zhao , Yu Fu , Tao Zhou

We propose a novel second-order optimization framework for training the emerging deep continuous-time models, specifically the Neural Ordinary Differential Equations (Neural ODEs). Since their training already involves expensive gradient…

Machine Learning · Computer Science 2021-11-09 Guan-Horng Liu , Tianrong Chen , Evangelos A. Theodorou

Painleve analysis and the singular manifold method are the tools used in this paper to perform a complete study of an equation in 2+1 dimensions. This procedure has allowed us to obtain the Lax pair, Darboux transformation and tau functions…

solv-int · Physics 2007-05-23 Pilar Garcia Estevez

We describe a set of Gaussian Process based approaches that can be used to solve non-linear Ordinary Differential Equations. We suggest an explicit probabilistic solver and two implicit methods, one analogous to Picard iteration and the…

Methodology · Statistics 2014-08-19 David Barber

Anomalous diffusion is a phenomenon that cannot be modeled accurately by second-order diffusion equations, but is better described by fractional diffusion models. The nonlocal nature of the fractional diffusion operators makes substantially…

Numerical Analysis · Mathematics 2018-03-08 K. Mustapha , K. Furati , O. M. Knio , O. Le Maitre

A development of an inverse first-order divided difference operator for functions of several variables is presented. Two generalized derivative-free algorithms builded up from Ostrowski's method for solving systems of nonlinear equations…

Numerical Analysis · Mathematics 2011-10-12 Miquel Grau-Sánchez , Miquel Noguera , Sergio Amat

The potentials for a one dimensional Schroedinger equation that are displaced along the x axis under second order Darboux transformations, called 2-SUSY invariant, are characterized in terms of a differential-difference equation. The…

Quantum Physics · Physics 2009-11-10 B F Samsonov , M L Glasser , J Negro , L M Nieto

A new approach for obtaining the transformations of solutions of nonlinear ordinary differential equations representable as the compatibility condition of the overdetermined linear systems is proposed. The corresponding transformations of…

Mathematical Physics · Physics 2009-10-31 N. V. Ustinov

A typical system of k difference (or differential) equations can be compressed, or folded into a difference (or ordinary differential) equation of order k. Such foldings appear in control theory as the canonical forms of the controllability…

Dynamical Systems · Mathematics 2014-03-18 H. Sedaghat

In the present work, an attempted was made to develop a numerical algorithm by the use of new orthogonal hybrid functions formed from hybrid of piecewise constant orthogonal sample-and-hold functions and piecewise linear orthogonal…

Numerical Analysis · Mathematics 2018-01-23 Seshu Kumar Damarla , Madhusree Kundu

Solving analytic systems using inversion can be implemented in a variety of ways. One method is to use Lagrange inversion and variations. Here we present a different approach, based on dual vector fields. For a function analytic in a…

Classical Analysis and ODEs · Mathematics 2011-02-11 Ph. Feinsilver , R. Schott

In this paper, we present a new numerical method to solve fractional differential equations. Given a fractional derivative of arbitrary real order, we present an approximation formula for the fractional operator that involves integer-order…

Numerical Analysis · Mathematics 2015-12-16 Ricardo Almeida , Nuno R. O. Bastos

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

In this paper, two kinds of high-order compact finite difference schemes for second-order derivative are developed. Then a second-order numerical scheme for Riemann-Liouvile derivative is established based on fractional center difference…

Numerical Analysis · Mathematics 2016-11-22 Hengfei Ding , Changpin Li

Discovering symbolic differential equations from data uncovers fundamental dynamical laws underlying complex systems. However, existing methods often struggle with the vast search space of equations and may produce equations that violate…

Machine Learning · Computer Science 2026-03-11 Jianke Yang , Manu Bhat , Bryan Hu , Yadi Cao , Nima Dehmamy , Robin Walters , Rose Yu