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This paper investigates a numerical probabilistic method for the solution of some semilinear stochastic partial differential equations (SPDEs in short). The numerical scheme is based on discrete time approximation for solutions of systems…

Probability · Mathematics 2015-09-21 Achref Bachouch , Mohamed Anis Ben Lasmar , Anis Matoussi , Mohamed Mnif

In this paper, enlightened by the asymptotic expansion methodology developed by Li(2013b) and Li and Chen (2016), we propose a Taylor-type approximation for the transition densities of the stochastic differential equations (SDEs) driven by…

Computational Finance · Quantitative Finance 2020-03-16 Fan Jiang , Xin Zang , Jingping Yang

In this paper we consider multi-dimensional partial differential equations of parabolic type involving divergence form operators that possess a discontinuous coefficient matrix along some smooth interface. The solution of the equation is…

Probability · Mathematics 2020-03-27 Pierre Etore , Miguel Martinez

We discuss a system of stochastic differential equations with a stiff linear term and additive noise driven by fractional Brownian motions (fBms) with Hurst parameter H>1/2, which arise e. g., from spatial approximations of stochastic…

Probability · Mathematics 2024-05-10 Minoo Kamrani , Kristian Debrabant , Nahid Jamshidi

This paper presents and analyzes the compensated projected Euler-Maruyama method for stochastic differential equations with jumps under a global monotonicity condition. Compared with existing conditions, this condition allows the…

Numerical Analysis · Mathematics 2018-12-11 Min Li , Chengming Huang

We devise an iterative scheme for numerically calculating dynamical two-point correlation functions in integrable many-body systems, in the Eulerian scaling limit. Expressions for these were originally derived in Ref. [1] by combining the…

Statistical Mechanics · Physics 2021-01-01 Frederik S. Møller , Gabriele Perfetto , Benjamin Doyon , Jörg Schmiedmayer

Viewing optimization methods as numerical integrators for ordinary differential equations (ODEs) provides a thought-provoking modern framework for studying accelerated first-order optimizers. In this literature, acceleration is often…

Optimization and Control · Mathematics 2021-02-24 Peiyuan Zhang , Antonio Orvieto , Hadi Daneshmand , Thomas Hofmann , Roy Smith

We present strongly convergent explicit and semi-implicit adaptive numerical schemes for systems of stiff stochastic differential equations (SDEs) where both the drift and diffusion are non-globally Lipschitz continuous. This stiffness may…

Numerical Analysis · Mathematics 2021-06-02 Cónall Kelly , Gabriel Lord

ODE solvers with randomly sampled timestep sizes appear in the context of chaotic dynamical systems, differential equations with low regularity, and, implicitly, in stochastic optimisation. In this work, we propose and study the stochastic…

Numerical Analysis · Mathematics 2024-08-05 Jonas Latz

In this paper we deal with pointwise approximation of solutions of stochastic differential equations (SDEs) driven by infinite dimensional Wiener process with additional jumps generated by Poisson random measure. The further investigations…

Probability · Mathematics 2022-05-04 Paweł Przybyłowicz , Michał Sobieraj , Łukasz Stȩpień

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

An implicit Euler--Maruyama method with non-uniform step-size applied to a class of stochastic partial differential equations is studied. A spectral method is used for the spatial discretization and the truncation of the Wiener process. A…

Numerical Analysis · Mathematics 2018-04-11 Yoshihito Kazashi

Given a smooth R^d-valued diffusion, we study how fast the Euler scheme with time step 1/n converges in law. To be precise, we look for which class of test functions f the approximate expectation E[f(X^{n,x}_1)] converges with speed 1/n to…

Probability · Mathematics 2007-07-10 Julien Guyon

The Parareal algorithm is used to solve time-dependent problems considering multiple solvers that may work in parallel. The key feature is a initial rough approximation of the solution that is iteratively refined by the parallel solvers. We…

Systems and Control · Computer Science 2014-02-18 Loïc Michel

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

By using absolutely continuous lower bounds of the L\'evy measure, explicit gradient estimates are derived for the semigroup of the corresponding L\'evy process with a linear drift. A derivative formula is presented for the conditional…

Probability · Mathematics 2011-03-16 Feng-Yu Wang

Parareal algorithms are studied for semilinear parabolic stochastic partial differential equations. These algorithms proceed as two-level integrators, with fine and coarse schemes, and have been designed to achieve a `parallel in real time'…

Numerical Analysis · Mathematics 2019-02-15 Charles-Edouard Bréhier , Xu Wang

In this note we consider stochastic differential equations driven by fractional Brownian motions (fBm) with Hurst parameter $H>1/3$. We prove that the corresponding modified Euler scheme and its Malliavin derivatives are integrable,…

Probability · Mathematics 2023-07-14 Jorge León , Yanghui Liu , Samy Tindel

We construct a finite element like scheme for fully non-linear integro-partial differential equations arising in optimal control of jump-processes. Special cases of these equations include optimal portfolio and option pricing equations in…

Numerical Analysis · Mathematics 2008-05-22 Fabio Camilli , Espen R. Jakobsen

Here we present well-posedness results for first order stochastic differential inclusions, more precisely for sweeping process with a stochastic perturbation. These results are provided in combining both deterministic sweeping process…

Analysis of PDEs · Mathematics 2014-03-31 Frederic Bernicot , Juliette Venel