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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

Adiabatic Quantum Computing relies on the quantum adiabatic theorem, which states that a quantum system evolves along its ground state with time if the governing Hamiltonian varies infinitely slowly. However, practical limitations force…

The classical state-space approach to optimal estimation of stochastic processes is efficient when the driving noises are generated by martingales. In particular, the weight function of the optimal linear filter, which solves a complicated…

Probability · Mathematics 2022-06-13 D. Afterman , P. Chigansky , M. Kleptsyna , D. Marushkevych

We study some functional inequalities satisfied by the distribution of the solution of a stochastic differential equation driven by fractional Brownian motions. Such functional inequalities are obtained through new integration by parts…

Probability · Mathematics 2011-02-23 Fabrice Baudoin , Cheng Ouyang

We study the law of the solution to the stochastic heat equation with additive Gaussian noise which behaves as the fractional Brownian motion in time and is white in space. We prove a decomposition of the solution in terms of the…

Probability · Mathematics 2011-10-13 Solesne Bourguin , Ciprian A. Tudor

In this paper we prove, for small Hurst parameters, the higher order differentiability of a stochastic flow associated with a stochastic differential equation driven by an additive multi-dimensional fractional Brownian noise, where the…

Probability · Mathematics 2018-05-15 Oussama Amine , David R. Baños , Frank Proske

We consider the numerical approximation of the mild solution to a semilinear stochastic wave equation driven by additive noise. For the spatial approximation we consider a standard finite element method and for the temporal approximation, a…

Numerical Analysis · Mathematics 2023-12-06 Mihály Kovács , Annika Lang , Andreas Petersson

In this work, we use the spectral Galerkin method to prove the existence of a pathwise unique mild solution of a fractional stochastic partial differential equation of Burgers type in a H\"older space. We get the temporal regularity and…

Analysis of PDEs · Mathematics 2017-12-29 Zineb Arab , Latifa Debbi

In this article, we develop and analyze a full discretization, based on the spatial spectral Galerkin method and the temporal drift implicit Euler scheme, for the stochastic Cahn--Hilliard equation driven by multiplicative space-time white…

Numerical Analysis · Mathematics 2020-06-22 Jianbo Cui , Jialin Hong

Numerical approximation of a stochastic partial integro-differential equation driven by a space- time white noise is studied by truncating a series representation of the noise, with finite element method for spatial discretization and…

Numerical Analysis · Mathematics 2017-11-07 Max Gunzburger , Buyang Li , Jilu Wang

Let $B=(B_1(t),\ldots,B_d(t))$ be a $d$-dimensional fractional Brownian motion with Hurst index $\alpha<1/4$. Defining properly iterated integrals of $B$ is a difficult task because of the low H\"older regularity index of its paths. Yet…

Probability · Mathematics 2010-06-08 J. Magnen , J. Unterberger

We study the stochastic total variation flow (STVF) equation with linear multiplicative noise. By considering a limit of a sequence of regularized stochastic gradient flows with respect to a regularization parameter $\varepsilon$ we obtain…

Numerical Analysis · Mathematics 2022-11-14 Ľubomír Baňas , Michael Röckner , André Wilke

We study a class of stochastic semilinear damped wave equations driven by additive Wiener noise. Owing to the damping term, under appropriate conditions on the nonlinearity, the solution admits a unique invariant distribution. We apply…

Numerical Analysis · Mathematics 2023-06-27 Ziyi Lei , Charles-Edouard Bréhier , Siqing Gan

We introduce the stochastic process of incremental multifractional Brownian motion (IMFBM), which locally behaves like fractional Brownian motion with a given local Hurst exponent and diffusivity. When these parameters change as function of…

Statistical Mechanics · Physics 2023-07-27 Jakub Slezak , Ralf Metzler

The rate of strong convergence is investigated for an approximation scheme for a class of stochastic differential equations driven by a time-changed Brownian motion, where the random time changes $(E_t)_{t\ge 0}$ considered include the…

Probability · Mathematics 2020-03-02 Sixian Jin , Kei Kobayashi

In this work it is shown how the immersed boundary method of (Peskin2002) for modeling flexible structures immersed in a fluid can be extended to include thermal fluctuations. A stochastic numerical method is proposed which deals with…

Soft Condensed Matter · Physics 2023-02-28 P. J. Atzberger , P. R. Kramer , C. S. Peskin

Fractional Brownian motion (FBM), a non-Markovian self-similar Gaussian stochastic process with long-ranged correlations, represents a widely applied, paradigmatic mathematical model of anomalous diffusion. We report the results of…

Fractional calculus provides a rigorous mathematical framework to describe anomalous stochastic processes by generalizing the notion of classical differential equations to their fractional-order counterparts. By introducing the fractional…

Numerical Analysis · Mathematics 2018-06-04 Ehsan Kharazmi , Mohsen Zayernouri

The effective diffusion of Brownian particles in periodic potential has been a central topic in nonequilibrium statistical physcis. A classical result is the Lifson formula which provides the effective diffusion constant in periodic…

Statistical Mechanics · Physics 2026-01-22 Sang Yang , Zhixin Peng

We study a class of semi-implicit Taylor-type numerical methods that are easy to implement and designed to solve multidimensional stochastic differential equations driven by a general rough noise, e.g. a fractional Brownian motion. In the…

Numerical Analysis · Mathematics 2020-06-25 Sebastian Riedel , Yue Wu