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We study pathwise approximation of scalar stochastic differential equations at a single time point or globally in time by means of methods that are based on finitely many observations of the driving Brownian motion. We prove lower error…

Numerical Analysis · Mathematics 2017-10-25 Mario Hefter , André Herzwurm , Thomas Müller-Gronbach

The existence of random attractors for singular stochastic partial differential equations (SPDE) perturbed by general additive noise is proven. The drift is assumed only to satisfy the standard assumptions of the variational approach to…

Probability · Mathematics 2011-11-02 Benjamin Gess

Stochastic averaging for a class of stochastic differential equations (SDEs) with fractional Brownian motion, of the Hurst parameter H in the interval (1/2, 1), is investigated. An averaged SDE for the original SDE is proposed, and their…

Dynamical Systems · Mathematics 2013-01-22 Yong Xu , Rong Guo , Di Liu , Huiqing Zhang , Jinqiao Duan

Fractional Brownian motion (fBm) is a canonical model for long-memory phenomena. In the presence of large amounts of potentially memory-bearing data, the data are often averaged, which can change the structure of the underlying…

We investigate the problem of the rate of convergence to equilibrium for ergodic stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H\in (1/3,1)$ and multiplicative noise component $\sigma$. When…

Probability · Mathematics 2016-10-05 Aurélien Deya , Fabien Panloup , Samy Tindel

Recently, it has been shown in [Hairer, M., Hutzenthaler, M., Jentzen, A., Loss of regularity for Kolmogorov equations, Ann. Probab. 43, 2 (2015), 468--527] that there exists a system of stochastic differential equations (SDE) on the time…

Probability · Mathematics 2016-09-27 Larisa Yaroslavtseva

This article offers sharp spatial and temporal mean-square regularity results for a class of semi-linear parabolic stochastic partial differential equations (SPDEs) driven by infinite dimensional fractional Brownian motion with the Hurst…

Numerical Analysis · Mathematics 2020-08-04 Xiaojie Wang , Ruisheng Qi , Fengze Jiang

We introduce the notion of stochastic logarithmic Lipschitz constants and use these constants to characterize stochastic contractivity of It\^o stochastic differential equations (SDEs) with multiplicative noise. We find an upper bound for…

Systems and Control · Electrical Eng. & Systems 2021-11-08 Zahra Aminzare

This work contributes to the limited literature on estimating the diffusivity or drift coefficient of nonlinear SPDEs driven by additive noise. Assuming that the solution is measured locally in space and over a finite time interval, we show…

Statistics Theory · Mathematics 2022-09-12 Randolf Altmeyer , Igor Cialenco , Gregor Pasemann

This work investigates radial solutions for nonlinear fractional Schr\"odinger equations driven by multiplicative noise. Leveraging radial deterministic and stochastic Strichartz estimates, we establish local well-posedness in the…

Analysis of PDEs · Mathematics 2025-06-03 Ao Zhang , Yanjie Zhang , Jinqiao Duan

The aim of this work is to provide the strong convergence results of numerical approximations of a general second order non-autonomous semilinear stochastic partial differential equation (SPDE) driven simultaneously by an additive…

Numerical Analysis · Mathematics 2024-09-11 Aurelien Junior Noupelah , Jean Daniel Mukam , Antoine Tambue

A stochastic linear transport equation with multiplicative noise is considered and the question of no-blow-up is investigated. The drift is assumed only integrable to a certain power. Opposite to the deterministic case where smooth initial…

Probability · Mathematics 2013-03-19 Ennio Fedrizzi , Franco Flandoli

In this paper, a solution is given to reflected backward doubly stochastic differential equations when the barrier is not necessarily right-continuous, and the noise is driven by two independent Brownian motions and an independent Poisson…

Probability · Mathematics 2020-06-29 Mohamed Marzougue , Yaya Sagna

Stochastic differential equations (SDEs) provide a natural framework for modelling intrinsic stochasticity inherent in many continuous-time physical processes. When such processes are observed in multiple individuals or experimental units,…

Computation · Statistics 2016-05-19 Gavin A. Whitaker , Andrew Golightly , Richard J. Boys , Chris Sherlock

Existence, uniqueness, and $L_p$-approximation results are presented for scalar stochastic differential equations (SDEs) by considering the case where, the drift coefficient has finitely many spatial discontinuities while both coefficients…

Probability · Mathematics 2022-04-06 Thomas Müller-Gronbach , Sotirios Sabanis , Larisa Yaroslavtseva

In this paper we consider stochastic Fokker-Planck Partial Differential Equations (PDEs), obtained as the mean-field limit of weakly interacting particle systems subjected to both independent (or idiosyncratic) and common Brownian noises.…

Probability · Mathematics 2024-05-17 François Delarue , Etienne Tanré , Raphaël Maillet

We build and study a data-driven procedure for the estimation of the stationary density f of an additive fractional SDE. To this end, we also prove some new concentrations bounds for discrete observations of such dynamics in stationary…

Probability · Mathematics 2020-03-12 Karine Bertin , Nicolas Klutchnikoff , Fabien Panloup , Maylis Varvenne

In this paper, we study dimension reduction techniques for large-scale controlled stochastic differential equations (SDEs). The drift of the considered SDEs contains a polynomial term satisfying a one-sided growth condition. Such…

Probability · Mathematics 2023-03-10 Martin Redmann

We introduce order-based diffusion processes as the solutions to multidimensional stochastic differential equations, with drift coefficient depending only on the ordering of the coordinates of the process and diffusion matrix proportional…

Probability · Mathematics 2014-03-11 Benjamin Jourdain , Julien Reygner

Diffusion with stochastic transport is investigated here when the random driving process is a very general Gaussian process, including Fractional Brownian motion. The purpose is the comparison with a deterministic PDE, which in certain…

Probability · Mathematics 2026-04-20 Franco Flandoli , Francesco Russo
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