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We propose a geometric numerical analysis of SDEs admitting Lie symmetries which allows us to individuate a symmetry adapted coordinates system where the given SDE has notable invariant properties. An approximation scheme preserving the…

Probability · Mathematics 2020-08-04 Francesco C. De Vecchi , Andrea Romano , Stefania Ugolini

We write expressions connected with numerical differentiation formulas of order $2$ in the form of Stieltjes integral, then we use Ohlin lemma and Levin-Stechkin theorem to study inequalities connected with these expressions. In particular,…

Classical Analysis and ODEs · Mathematics 2016-09-01 Tomasz Szostok

Some new integrals involving the Stieltjes constants are developed in this paper.

Classical Analysis and ODEs · Mathematics 2011-04-12 Donal F. Connon

The objective of this paper is to prove the convergence of a linear implicit multi-step numerical method for ordinary differential equations. The algorithm is obtained via Taylor approximations. The convergence is proved following the…

Chaotic Dynamics · Physics 2011-03-08 Marius-F. Danca

In this work we develop a theory of Stieltjes-analytic functions. We first define the Stieltjes monomials and polynomials and we study them exhaustively. Then, we introduce the Stieltjes analytic functions locally, as an infinite series of…

Classical Analysis and ODEs · Mathematics 2025-07-08 Víctor Cora , F. Javier Fernández , F. Adrián F. Tojo

We show that a differential version of the classical Chebyshev-Markov-Stieltjes inequalities holds for a broad family of weight functions. Such a differential version appears to be new. Our results apply to weight functions which are…

Classical Analysis and ODEs · Mathematics 2017-03-14 Shoni Gilboa , Ron Peled

We construct a nonstandard finite difference numerical scheme to approximate stochastic differential equations (SDEs) using the idea of weighed step introduced by R.E. Mickens. We prove the strong convergence of our scheme under locally…

Numerical Analysis · Mathematics 2015-07-23 Frédéric Pierret

A simple yet effective numerical method using orthogonal hybrid functions consisting of piecewise constant orthogonal sample-and-hold functions and piecewise linear orthogonal triangular functions is proposed to solve numerically fractional…

Numerical Analysis · Mathematics 2018-02-01 Seshu Kumar Damarla , Madhusree Kundu

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 introduce a new numerical method, based on Bernoulli polynomials, for solving multiterm variable-order fractional differential equations. The variable-order fractional derivative was considered in the Caputo sense, while the…

Numerical Analysis · Mathematics 2021-11-18 Somayeh Nemati , Pedro M. Lima , Delfim F. M. Torres

A new method for solving numerically stochastic partial differential equations (SPDEs) with multiple scales is presented. The method combines a spectral method with the heterogeneous multiscale method (HMM) presented in [W. E, D. Liu, and…

Numerical Analysis · Mathematics 2015-05-28 A. Abdulle , G. A. Pavliotis

This work focuses on the numerical approximations of random periodic solutions of stochastic differential equations (SDEs). Under non-globally Lipschitz conditions, we prove the existence and uniqueness of random periodic solutions for the…

Numerical Analysis · Mathematics 2024-06-21 Ziheng Chen , Liangmin Cao , Lin Chen

Formulated is a new systematic method for obtaining higher order corrections in numerical simulation of stochastic differential equations (SDEs), i.e., Langevin equations. Random walk step algorithms within a given order of finite $\Delta…

High Energy Physics - Lattice · Physics 2009-10-28 H. Nakajima , S. Furui

In this work, we study the numerical approximation of a class of singular fully coupled forward backward stochastic differential equations. These equations have a degenerate forward component and non-smooth terminal condition. They are…

Numerical Analysis · Mathematics 2022-08-17 Jean-François Chassagneux , Mohan Yang

We present effective numerical algorithms for locally recovering unknown governing differential equations from measurement data. We employ a set of standard basis functions, e.g., polynomials, to approximate the governing equation with high…

Numerical Analysis · Mathematics 2020-05-05 Kailiang Wu , Dongbin Xiu

A new method for solving non-autonomous ordinary differential equations is proposed, the method achieves spectral accuracy. It is based on a new result which expresses the solution of such ODEs as an element in the so called…

Numerical Analysis · Mathematics 2022-10-03 Stefano Pozza , Niel Van Buggenhout

This paper gives the existence and uniqueness results for solution of fractional differential equations with Hilfer derivative. Using some new techniques and generalizing the restrictive conditions imposed on considered function, the…

Classical Analysis and ODEs · Mathematics 2017-09-29 D. B. Dhaigude , Sandeep P. Bhairat

We consider a linear partial integro-differential equation that arises in the modeling of various physical and biological processes. We study the problem in a spatial periodic domain. We analyze numerical stability and numerical convergence…

Numerical Analysis · Mathematics 2010-05-31 Samir Kumar Bhowmik

We present a class of new explicit and stable numerical algorithms to solve the spatially discretized linear heat or diffusion equation. After discretizing the space and the time variables like conventional finite difference methods, we do…

Numerical Analysis · Mathematics 2021-04-27 Endre Kovács

Material response of real, passive, linear, time-invariant media to external influences is described by complex analytic functions of frequency that can always be written in terms of Stieltjes functions -- a special class of analytic…

Optimization and Control · Mathematics 2022-03-25 Yury Grabovsky
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