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A new numerical method is devised and analyzed for a type of ill-posed elliptic Cauchy problems by using the primal-dual weak Galerkin finite element method. This new primal-dual weak Galerkin algorithm is robust and efficient in the sense…

Numerical Analysis · Mathematics 2018-09-14 Chunmei Wang

Classical approximation results for stochastic differential equations analyze the $L^p$-distance between the exact solution and its Euler-Maruyama approximations. In this article we measure the error with temporal-spatial H\"older-norms.…

Numerical Analysis · Mathematics 2022-04-11 Tuan Anh Nguyen , Martin Hutzenthaler

We review $H^{1}$-well-posedness for initial value problems of ordinary differential equations with state-dependent right-hand side. We streamline known approaches to infer existence and uniqueness of solutions for small times given a…

Classical Analysis and ODEs · Mathematics 2024-10-29 Bernhard Aigner , Marcus Waurick

In this paper, we propose a class of explicit positivity preserving numerical methods for general stochastic differential equations which have positive solutions. Namely, all the numerical solutions are positive. Under some reasonable…

Numerical Analysis · Mathematics 2021-06-30 Yulian Yi , Yaozhong Hu , Jingjun Zhao

This article discusses a unified convergence analysis of the semilinear time-dependent equation $\partial_t u + (-1)^\mathrm{m}\Delta^{\mathrm{m}}u + u^3 - u = f$ with $\mathrm{m} \in \{1,2\}$ and homogeneous Dirichlet boundary conditions.…

Analysis of PDEs · Mathematics 2026-05-12 Gopikrishnan Chirappurathu Remesan

We consider the numerical approximation of a general second order semi--linear parabolic stochastic partial differential equation (SPDE) driven by additive space-time noise. We introduce a new modified scheme using a linear functional of…

Numerical Analysis · Mathematics 2016-07-20 Gabriel J Lord , Antoine Tambue

This paper studies the weak convergence order of the stochastic theta method for stochastic differential equations (SDEs) driven by time-changed L\'{e}vy noise under global Lipschitz and linear growth conditions. In contrast to classical…

Numerical Analysis · Mathematics 2026-03-31 Ziheng Chen , Jiao Liu , Meng Cai

In this article, we construct and analyse an explicit numerical splitting method for a class of semi-linear stochastic differential equations (SDEs) with additive noise, where the drift is allowed to grow polynomially and satisfies a global…

Numerical Analysis · Mathematics 2022-02-04 Evelyn Buckwar , Adeline Samson , Massimiliano Tamborrino , Irene Tubikanec

We consider the mathematical analysis and numerical approximation of a system of nonlinear partial differential equations that arises in models that have relevance to steady isochoric flows of colloidal suspensions. The symmetric velocity…

Numerical Analysis · Mathematics 2021-08-09 Andrea Bonito , Vivette Girault , Diane Guignard , Kumbakonam R. Rajagopal , Endre Süli

We study linear integro-differential equations in Hilbert spaces with operator-valued kernels and give sufficient conditions for the well-posedness. We show that several types of integro-differential equations are covered by the class of…

Analysis of PDEs · Mathematics 2016-04-05 Sascha Trostorff

Consider the following stochastic differential equation (SDE) $$dX_t = b(t,X_{t-}) \, dt+ dL_t, \quad X_0 = x,$$ driven by a $d$-dimensional L\'evy process $(L_t)_{t \geq 0}$. We establish conditions on the L\'evy process and the drift…

Probability · Mathematics 2020-05-01 Franziska Kühn , René L. Schilling

This paper investigates the approximation of invariant measures for McKean-Vlasov stochastic differential equations (SDEs) using the Euler-Maruyama (EM) scheme under a monotonicity condition. Firstly, the convergence of the numerical…

Probability · Mathematics 2026-04-17 Zhen Wang , Mingyan Wu

In this paper we investigate explicit numerical approximations for stochastic differential delay equations (SDDEs) under a local Lipschitz condition by employing the adaptive Euler-Maruyama (EM) method. Working in both finite and infinite…

Probability · Mathematics 2023-08-31 Ulises Botija-Munoz , Chenggui Yuan

The aim of this paper is to construct and analyze explicit exponential Runge-Kutta methods for the temporal discretization of linear and semilinear integro-differential equations. By expanding the errors of the numerical method in terms of…

Numerical Analysis · Mathematics 2023-01-24 Alexander Ostermann , Fardin Saedpanah , Nasrin Vaisi

We discretize the stochastic Allen-Cahn equation with additive noise by means of a spectral Galerkin method in space and a tamed version of the exponential Euler method in time. The resulting error bounds are analyzed for the…

Numerical Analysis · Mathematics 2021-01-20 Meng Cai , Siqing Gan , Xiaojie Wang

A practical and new Runge--Kutta numerical scheme for stochastic differential equations is explored. Numerical examples demonstrate the strong convergence of the method. The first order strong convergence is then proved using Ito integrals…

Numerical Analysis · Mathematics 2012-10-04 A. J. Roberts

Previously, the authors derived an analog of the Euler-Maru\-yama method (fEMM) for free stochastic differential equations (fSDEs) and proved strong convergence of order $\gamma=0.5$ in $L_1(\varphi)$-norm under certain assumptions. In this…

Probability · Mathematics 2026-03-31 Michael Wibmer , Georg Schlüchtermann

In this paper we discuss the adjoint stabilised finite element method introduced in, E. Burman, Stabilized finite element methods for nonsymmetric, noncoercive and ill-posed problems. Part I: elliptic equations, SIAM Journal on Scientific…

Numerical Analysis · Mathematics 2015-12-10 Erik Burman

In this paper, we consider a class of stochastic differential equations driven by symmetric non-degenerate $\alpha$-stable processes (including cylindrical ones) with $\alpha \in (1,2)$. We first establish a quantitative estimate for the…

Probability · Mathematics 2026-04-10 Zimo Hao , Mingyan Wu

It is well known that the Euler method for a random ordinary differential equation $\mathrm{d}X_t/\mathrm{d}t = f(t, X_t, Y_t)$ driven by a stochastic process $\{Y_t\}_t$ with $\theta$-H\"older sample paths is estimated to be of strong…

Probability · Mathematics 2025-10-21 Peter E. Kloeden , Ricardo M. S. Rosa