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Welcome to a beautiful subject in scientific computing: numerical solution of ordinary differential equations (ODEs) with initial conditions.

History and Overview · Mathematics 2024-12-31 Davoud Mirzaei

The analysis of many physical phenomena can be reduced to the study of solutions of differential equations with polynomial coefficients. In the present work, we establish the necessary and sufficient conditions for the existence of…

Classical Analysis and ODEs · Mathematics 2020-03-19 Kyle R. Bryenton1 , Andrew R. Cameron , Keegan L. A. Kirk , Nasser Saad , Patrick Strongman , Nikita Volodin

We study the problem of estimating the coefficients in linear ordinary differential equations (ODE's) with a diverging number of variables when the solutions are observed with noise. The solution trajectories are first smoothed with local…

Statistics Theory · Mathematics 2008-04-29 Heng Lian

Infinitely many explicit solutions of certain second-order differential equations with an apparent singularity of characteristic exponent -2 are constructed by adjusting the parameter of the multi-indexed Laguerre polynomials.

Classical Analysis and ODEs · Mathematics 2012-11-16 Ryu Sasaki , Kouichi Takemura

We extend the shell and kernel reductions for hyperexponential functions over the field of rational functions to a monomial extension. Both of the reductions are incorporated into one algorithm. As an application, we present an additive…

Symbolic Computation · Computer Science 2023-10-03 Shaoshi Chen , Hao Du , Yiman Gao , Ziming Li

The aim of this paper is to give two new algorithms, which are elimination free, to find polynomial and rational solutions for a given holonomic system associated to a set of linear differential operators in the Weyl algebra D = k<x_1, ...,…

Algebraic Geometry · Mathematics 2007-05-23 T. Oaku , N. Takayama , H. Tsai

We present numerical solutions for differential equations by expanding the unknown function in terms of Chebyshev polynomials and solving a system of linear equations directly for the values of the function at the extrema (or zeros) of the…

Computational Physics · Physics 2009-10-31 Bogdan Mihaila , Ioana Mihaila

We consider a system of differential equations and obtain its solutions with exponential asymptotics and analyticity with respect to the spectral parameter. Solutions of such type have importance in studying spectral properties of…

Classical Analysis and ODEs · Mathematics 2024-05-09 Maria Kuznetsova

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

In this paper we construct high order numerical methods for solving third and fourth orders nonlinear functional differential equations (FDE). They are based on the discretization of iterative methods on continuous level with the use of the…

Numerical Analysis · Mathematics 2024-11-05 Dang Quang A , Dang Quang Long

We present a quantum algorithm for systems of (possibly inhomogeneous) linear ordinary differential equations with constant coefficients. The algorithm produces a quantum state that is proportional to the solution at a desired final time.…

Quantum Physics · Physics 2017-11-07 Dominic W. Berry , Andrew M. Childs , Aaron Ostrander , Guoming Wang

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

A generalized exponential matrix based on the construction of kernel operators for generalized summability is defined and analyzing its main properties, generalizing the classical exponential matrix and fractional exponential matrix. This…

Classical Analysis and ODEs · Mathematics 2023-05-08 Alberto Lastra , Cruz Prisuelos-Arribas

High index differential algebraic equations (DAEs) are ordinary differential equations (ODEs) with constraints and arise frequently from many mathematical models of physical phenomenons and engineering fields. In this paper, we generalize…

Symbolic Computation · Computer Science 2015-04-21 Xiaolin Qin , Lu Yang , Yong Feng , Bernhard Bachmann , Peter Fritzson

A polynomial algorithm is obtained for the NP-complete linear ordering problem.

Computational Complexity · Computer Science 2007-05-23 Givi Bolotashvili

We present an algorithm for computing a separating linear form of a system of bivariate polynomials with integer coefficients, that is a linear combination of the variables that takes different values when evaluated at distinct (complex)…

Symbolic Computation · Computer Science 2014-01-21 Yacine Bouzidi , Sylvain Lazard , Marc Pouget , Fabrice Rouillier

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

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

Let $\mathbb{R}$ be the field of real numbers. We consider the problem of computing the real isolated points of a real algebraic set in $\mathbb{R}^n$ given as the vanishing set of a polynomial system. This problem plays an important role…

Computational Geometry · Computer Science 2020-08-27 Huu Phuoc Le , Mohab Safey El Din , Timo de Wolff

Probabilistic numerical solvers for ordinary differential equations compute posterior distributions over the solution of an initial value problem via Bayesian inference. In this paper, we leverage their probabilistic formulation to…

Machine Learning · Statistics 2021-10-22 Nathanael Bosch , Filip Tronarp , Philipp Hennig
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