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We show that solutions of free stochastic differential equations with regular drifts and diffusion coefficients, when considered backwards in time, still satisfy free SDEs for an explicit free Brownian motion and drift. We also study the…

Probability · Mathematics 2014-02-20 Yoann Dabrowski

We study reaction diffusion equations with a deterministic reaction term as well as two random reaction terms, one that acts on the interior of the domain, and another that acts only on the boundary of the domain. We are interested in the…

Probability · Mathematics 2018-04-16 Sandra Cerrai , Nicholas Paskal

The scaled Brownian motion (SBM) is regarded as one of the paradigmatic random processes, featuring the anomalous diffusion property characterized by the diffusion exponent. It is a Gaussian, self-similar process with independent…

Probability · Mathematics 2024-04-29 Hubert Woszczek , Aleksei Chechkin , Agnieszka Wylomanska

In the first part of the paper we develop the sensitivity analysis for the nonlinear McKean-Vlasov diffusions stressing precise estimates of growth of solutions and their derivatives with respect to the initial data, under rather general…

Probability · Mathematics 2017-12-06 Vassili Kolokoltsov , Marianna Troeva

We develope a perturbation theory for stochastic differential equations (SDEs) by which we mean both stochastic ordinary differential equations (SODEs) and stochastic partial differential equations (SPDEs). In particular, we estimate the $…

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

In this paper we present stochastic foundations of fractional dynamics driven by fractional material derivative of distributed order-type. Before stating our main result we present the stochastic scenario which underlies the dynamics given…

Probability · Mathematics 2015-10-02 Marcin Magdziarz , Marek Teuerle

The origin of the long-range memory in the non-equilibrium systems is still an open problem as the phenomenon can be reproduced using models based on Markov processes. In these cases a notion of spurious memory is introduced. A good example…

Statistical Finance · Quantitative Finance 2017-08-01 Vygintas Gontis , Aleksejus Kononovicius

This paper is mainly concerned with a kind of fractional stochastic evolution equations driven by L\'evy noise in a bounded domain. We first state the well-posedness of the problem via iterative approximations and energy estimates. Then,…

Probability · Mathematics 2025-01-28 Jiaohui Xu , Tomás Caraballo , José Valero

In this paper, we answer a question posed by Kurt Johansson, to find a PDE for the joint distribution of the Airy Process. The latter is a continuous stationary process, describing the motion of the outermost particle of the Dyson Brownian…

Probability · Mathematics 2007-05-23 Mark Adler , Pierre van Moerbeke

We consider a class of dissipative stochastic differential equations (SDE's) with time-periodic coefficients in finite dimension, and the response of time-asymptotic probability measures induced by such SDE's to sufficiently regular, small…

Probability · Mathematics 2022-01-04 Michal Branicki , Kenneth Uda

It is well known, mainly because of the work of Kurtz, that density dependent Markov chains can be approximated by sets of ordinary differential equations (ODEs) when their indexing parameter grows very large. This approximation cannot…

Performance · Computer Science 2014-04-04 Marco Beccuti , Enrico Bibbona , Andras Horvath , Roberta Sirovich , Alessio Angius , Gianfranco Balbo

The Stochastic Partial Differential Equation (SPDE) approach, now commonly used in spatial statistics to construct Gaussian random fields, is revisited from a mechanistic perspective based on the movement of microscopic particles, thereby…

Methodology · Statistics 2021-11-11 Lionel Roques , Denis Allard , Samuel Soubeyrand

Stochastic differential equations (SDEs) are one of the most important representations of dynamical systems. They are notable for the ability to include a deterministic component of the system and a stochastic one to represent random…

Machine Learning · Computer Science 2021-05-19 Noura Dridi , Lucas Drumetz , Ronan Fablet

We study one-dimensional stochastic differential equations of form $dX_t = \sigma(X_t)dY_t$, where $Y$ is a suitable H\"older continuous driver such as the fractional Brownian motion $B^H$ with $H>\frac12$. The innovative aspect of the…

Probability · Mathematics 2019-08-09 Soledad Torres , Lauri Viitasaari

A large deviation principle is established for a two-scale stochastic system in which the slow component is a continuous process given by a small noise finite dimensional It\^{o} stochastic differential equation, and the fast component is a…

Probability · Mathematics 2017-05-09 Amarjit Budhiraja , Paul Dupuis , Arnab Ganguly

The random motion of a Brownian particle confined in some finite domain is considered. Quite generally, the relevant statistical properties involve infinite series, whose coefficients are related to the eigenvalues of the diffusion…

Statistical Mechanics · Physics 2010-04-26 Thomas Bickel

We unify and extend the semigroup and the PDE approaches to stochastic maximal regularity of time-dependent semilinear parabolic problems with noise given by a cylindrical Brownian motion. We treat random coefficients that are only…

Analysis of PDEs · Mathematics 2019-02-12 Pierre Portal , Mark Veraar

In this paper, we consider a multidimensional ergodic diffusion with jumps driven by a Brownian motion and a Poisson random measure associated with a pure-jump L\'evy process with finite L\'evy measure, whose drift coefficient depends on an…

Probability · Mathematics 2016-09-30 Arturo Kohatsu-Higa , Eulalia Nualart , Ngoc Khue Tran

We will consider the following stochastic differential equation (SDE): \begin{equation} X_t=X_0+\int_0^tb(X_s,\theta_0)ds+\sigma B_t,~~~t\in(0,T], \end{equation} where $\{B_t\}_{t\ge 0}$ is a fractional Brownian motion with Hurst index…

Statistics Theory · Mathematics 2021-12-24 Yasutaka Shimizu , Shohei Nakajima

This paper deals with the process $X = (X_t)_{t\in [0,T]}$ defined by the stochastic differential equation (SDE) $dX_t = (a(X_t) + b(Y_t))dt +\sigma(X_t)dW_1(t)$, where $W_1$ is a Brownian motion and $Y$ is an exogenous process. The first…

Statistics Theory · Mathematics 2025-07-09 Fabienne Comte , Nicolas Marie