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In this paper, we first propose an unconditionally stable implicit difference scheme for solving generalized time-space fractional diffusion equations (GTSFDEs) with variable coefficients. The numerical scheme utilizes the $L1$-type formula…

Numerical Analysis · Mathematics 2021-09-15 Xian-Ming Gu , Ting-Zhu Huang , Yong-Liang Zhao , Pin Lyu , Bruno Carpentieri

This paper concerns the convergence of an iterative scheme for 2D stochastic primitive equations on a bounded domain. The stochastic system is split into two equations: a deterministic 2D primitive equations with random initial value and a…

Probability · Mathematics 2019-07-09 Xuhui Peng , Rangrang Zhang

For many systems of differential equations modeling problems in science and engineering, there are natural splittings of the right hand side into two parts, one non-stiff or mildly stiff, and the other one stiff. For such systems…

Numerical Analysis · Computer Science 2013-04-09 Angelamaria Cardone , Zdzislaw Jackiewicz , Hong Zhang , Adrian Sandu

We show that Newton methods for generalized equations are input-to-state stable with respect to disturbances such as due to inexact computations. We then use this result to obtain convergence and robustness of a multistep Newton-type method…

Optimization and Control · Mathematics 2025-03-18 Torbjørn Cunis , Ilya Kolmanovsky

In [8], some exact splittings are proposed for inhomogeneous quadratic differential equations including, for example, transport equations, kinetic equations, and Schr{\"o}dinger type equations with a rotation term. In this work, these exact…

Numerical Analysis · Mathematics 2020-01-01 Joackim Bernier , Nicolas Crouseilles , Yingzhe Li

In this paper we established the condition for a curve to satisfy stochastic generalized fractional HP (Hamilton-Pontryagin) equations. These equations are described using Ito integral. We have also considered the case of stochastic…

Dynamical Systems · Mathematics 2009-09-01 I. D. Albu , M. Neamtu , D. Opris

We derive a new methodology for the construction of high order integrators for sampling the invariant measure of ergodic stochastic differential equations with dynamics constrained on a manifold. We obtain the order conditions for sampling…

Numerical Analysis · Mathematics 2022-08-31 Adrien Laurent , Gilles Vilmart

We study the Strang splitting scheme for quasilinear Schr\"odinger equations. We establish the convergence of the scheme for solutions with small initial data. We analyze the linear instability of the numerical scheme, which explains the…

Numerical Analysis · Mathematics 2014-09-22 Jianfeng Lu , Jeremy L. Marzuola

The Monte Carlo method is a thriving and mathematically beautiful numerical technique used extensively, nowadays, to deal with many demanding problems in diverse fields. Here, we present an iterative Monte Carlo algorithm to work out very…

Computational Physics · Physics 2024-08-02 Martín Chávez-Páez , Enrique González-Tovar , Guillermo Iván Guerrero-García

In this paper we present a perturbative procedure that allows one to numerically solve diffusive non-Markovian Stochastic Schr\"odinger equations, for a wide range of memory functions. To illustrate this procedure numerical results are…

Quantum Physics · Physics 2009-11-07 Jay Gambetta , H. M. Wiseman

This article analyses the convergence of the Lie-Trotter splitting scheme for the stochastic Manakov equation, a system arising in the study of pulse propagation in randomly birefringent optical fibers. First, we prove that the strong order…

Analysis of PDEs · Mathematics 2020-10-30 André Berg , David Cohen , Guillaume Dujardin

Recently, Stochastic Gradient Markov Chain Monte Carlo (SG-MCMC) methods have been proposed for scaling up Monte Carlo computations to large data problems. Whilst these approaches have proven useful in many applications, vanilla SG-MCMC…

Machine Learning · Statistics 2016-12-13 Umut Şimşekli , Roland Badeau , A. Taylan Cemgil , Gaël Richard

We introduce a new methodology based on the multirevolution idea for constructing integrators for stochastic differential equations in the situation where the fast oscillations themselves are driven by a Stratonovich noise. Applications…

Numerical Analysis · Mathematics 2020-02-04 Adrien Laurent , Gilles Vilmart

In this paper we address the numerical solution of nonlinear ill-posed systems by iterative regularization methods in the classes of Levenberg-Marquardt, trust-region and adaptive quadratic regularization procedures. Both with exact and…

Numerical Analysis · Mathematics 2015-04-17 Stefania Bellavia , Benedetta Morini

Runge-Kutta methods have an irreplaceable position among numerical methods designed to solve ordinary differential equations. Especially, implicit ones are suitable for approximating solutions of stiff initial value problems. We propose a…

Numerical Analysis · Mathematics 2024-12-13 Hana Mizerová , Katarína Tvrdá

This paper introduces an adaptive time splitting technique for the solution of stiff evolutionary PDEs that guarantees an effective error control of the simulation, independent of the fastest physical time scale for highly unsteady…

Numerical Analysis · Mathematics 2012-04-10 Stéphane Descombes , Max Duarte , Thierry Dumont , Violaine Louvet , Marc Massot

We establish a general theory of optimal strong error estimation for numerical approximations of a second-order parabolic stochastic partial differential equation with monotone drift driven by a multiplicative infinite-dimensional Wiener…

Numerical Analysis · Mathematics 2022-03-02 Zhihui Liu , Zhonghua Qiao

In this paper we propose a numerical scheme for partitioned systems of index 2 DAEs, such as those arising from nonholonomic mechanical problems and prove the order of a certain class of Runge-Kutta methods we call of Lobatto-type. The…

Numerical Analysis · Mathematics 2019-01-30 Rodrigo Takuro Sato Martín de Almagro

In this paper we consider splitting methods for nonlinear ordinary differential equations in which one of the (partial) flows that results from the splitting procedure can not be computed exactly. Instead, we insert a well-chosen state…

Numerical Analysis · Mathematics 2014-05-27 Lukas Einkemmer , Alexander Ostermann

In this paper, we consider stochastic Runge-Kutta methods for stochastic Hamiltonian partial differential equations and present some sufficient conditions for multisymplecticity of stochastic Runge-Kutta methods of stochastic Hamiltonian…

Symplectic Geometry · Mathematics 2018-03-02 Liying Zhang , Lihai Ji
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