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A probabilistic approach of computing geometric rate of convergence of stochastic processes is introduced in this paper. The goal is to quantitatively compute both upper and lower bounds of the exponential rate of convergence to the…

Dynamical Systems · Mathematics 2020-12-02 Yao Li , Shirou Wang

In this article we show that a finite dimensional stochastic differential equation driven by a L\'evy process can be formulated as a stochastic partial differential equation. We prove the existence and uniqueness of strong solutions of such…

Probability · Mathematics 2018-02-15 Suprio Bhar , Rajeev Bhaskaran , Barun Sarkar

The strong convergence of the semi-implicit Euler-Maruyama (EM) method for stochastic differential equations with non-linear coefficients driven by a class of L\'evy processes is investigated. The dependence of the convergence order of the…

Numerical Analysis · Mathematics 2023-11-21 Xiaotong Li , Wei Liu , Hongjiong Tian

In this article we develop a new abstract strategy for proving ergodicity with explicit computable rate of convergence for diffusions associated with a degenerate Kolmogorov operator L. A crucial point is that the evolution operator L may…

Functional Analysis · Mathematics 2016-01-04 Martin Grothaus , Patrik Stilgenbauer

We give a probabilistic numerical method for solving a partial differential equation with fractional diffusion and nonlinear drift. The probabilistic interpretation of this equation uses a system of particles driven by L\'evy alpha-stable…

Probability · Mathematics 2010-07-26 Benjamin Jourdain , Raphaël Roux

We study the rate of convergence of some recursive procedures based on some "exact" or "approximate" Euler schemes which converge to the invariant measure of an ergodic SDE driven by a L\'{e}vy process. The main interest of this work is to…

Probability · Mathematics 2007-05-23 Fabien Panloup

We prove the exponential ergodicity of the transition probabilities of solutions to elliptic multivalued stochastic differential equations.

Probability · Mathematics 2011-04-28 Jiagang Ren , Jing Wu , Xicheng Zhang

Many stochastic differential equations (SDEs) in the literature have a superlinearly growing nonlinearity in their drift or diffusion coefficient. Unfortunately, moments of the computationally efficient Euler-Maruyama approximation method…

Probability · Mathematics 2020-11-25 Martin Hutzenthaler , Arnulf Jentzen

We show that the rate of convergence of asymptotic expansions for solutions of SDEs is generally higher in the case of degenerate (or partial) diffusion compared to the elliptic case, i.e. it is higher when the Brownian motion directly acts…

Probability · Mathematics 2016-10-06 S. Pagliarani , A. Pascucci , M. Pignotti

Based on the explicit coupling property, the ergodicity and the exponential ergodicity of L\'{e}vy driven Ornstein-Uhlenbeck processes are established.

Probability · Mathematics 2012-05-22 Jian Wang

It has recently been demonstrated that locality of spatial supports in the parametrization of coefficients in elliptic PDEs can lead to improved convergence rates of sparse polynomial expansions of the corresponding parameter-dependent…

Numerical Analysis · Mathematics 2017-07-11 Markus Bachmayr , Albert Cohen , Dinh Dũng , Christoph Schwab

This article investigates the weak approximation towards the invariant measure of semi-linear stochastic differential equations (SDEs) under non-globally Lipschitz coefficients. For this purpose, we propose a linear-theta-projected Euler…

Numerical Analysis · Mathematics 2024-03-28 Chenxu Pang , Xiaojie Wang , Yue Wu

We derive moment estimates and a strong limit theorem for space inverses of stochastic flows generated by jump SDEs with adapted coefficients in weighted H\"older norms using the Sobolev embedding theorem and the change of variable formula.…

Probability · Mathematics 2014-11-25 James-Michael Leahy , Remigijus Mikulevicius

We consider the Euler scheme for stochastic differential equations with jumps, whose intensity might be infinite and the jump structure may depend on the position. This general type of SDE is explicitly given for Feller processes and a…

Probability · Mathematics 2020-04-17 Björn Böttcher , Alexander Schnurr

The problem of approximating the covariance operator of the mild solution to a linear stochastic partial differential equation is considered. An integral equation involving the semigroup of the mild solution is derived and a general error…

Numerical Analysis · Mathematics 2022-04-25 Mihály Kovács , Annika Lang , Andreas Petersson

This paper presents a rigorous numerical framework for computing multiple solutions of semilinear elliptic problems by spatiotemporal high-index saddle dynamics (HiSD), which extends the traditional HiSD to the continuous-in-space setting,…

Numerical Analysis · Mathematics 2026-01-14 Lei Zhang , Xiangcheng Zheng , Shangqin Zhu

We give a short proof of It\^o's formula for stochastic Hilbert-space valued processes in the setting $V\subset H\subset V^{*}$ based on the possibility to lift the stochastic differentials, which are originally in $V^{*}$, into $H$. Using…

Probability · Mathematics 2012-08-21 N. V. Krylov

Motivated by the results of \cite{sabanis2015}, we propose explicit Euler-type schemes for SDEs with random coefficients driven by L\'evy noise when the drift and diffusion coefficients can grow super-linearly. As an application of our…

Probability · Mathematics 2016-11-11 Chaman Kumar , Sotirios Sabanis

We consider the long-time behavior of an explicit tamed exponential Euler scheme applied to a class of parabolic semilinear stochastic partial differential equations driven by additive noise, under a one-sided Lipschitz continuity…

Numerical Analysis · Mathematics 2020-10-02 Charles-Edouard Bréhier

We consider the construction of semi-implicit linear multistep methods which can be applied to time dependent PDEs where the separation of scales in additive form, typically used in implicit-explicit (IMEX) methods, is not possible. As…

Numerical Analysis · Mathematics 2020-01-14 Giacomo Albi , Lorenzo Pareschi
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