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In this paper, we study a stochastic parabolic problem involving a nonlocal diffusion operator associated with nonlocal Robin-type boundary conditions. The stochastic dynamics under consideration are driven by a mixture of a classical…

Brownian yet non-Gaussian phenomenon has recently been observed in many biological and active matter systems. The main idea of explaining this phenomenon is to introduce a random diffusivity for particles moving in inhomogeneous…

Statistical Mechanics · Physics 2022-01-19 Xudong Wang , Yao Chen

In many physical or biological systems, diffusion can be described by Brownian motions with stochastic diffusion coefficients (DCs). In the present study, we investigate properties of the diffusion with a broad class of stochastic DCs with…

Statistical Mechanics · Physics 2024-06-13 Go Uchida , Hitoshi Washizu , Hiromi Miyoshi

Motivated by subdiffusive motion of bio-molecules observed in living cells we study the stochastic properties of a non-Brownian particle whose motion is governed by either fractional Brownian motion or the fractional Langevin equation and…

Statistical Mechanics · Physics 2016-09-08 Jae-Hyung Jeon , Ralf Metzler

The goal of this paper is to study the Moderate Deviation Principle (MDP) for a system of stochastic reaction-diffusion equations with a time-scale separation in slow and fast components and small noise in the slow component. Based on weak…

Probability · Mathematics 2022-02-03 Ioannis Gasteratos , Michael Salins , Konstantinos Spiliopoulos

We consider a diffusion equation in $\mathbb{R}^d$ with drift equal to the gradient of a homogeneous potential of degree $1+\gamma$, with $0<\gamma<1$, and local variance equal to $\varepsilon^2$ with $\varepsilon\to 0$. The associated…

Probability · Mathematics 2026-03-04 Paola Bermolen , Valeria Goicoechea , José R. León

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 study functional stochastic differential equations with a locally unbounded, functional drift focusing on well-posedness, stability and the strong Feller property. Following the non-functional case, we only consider integrability…

Probability · Mathematics 2020-09-08 Stefan Bachmann

The present work investigates the asymptotic behaviors, at the zero-noise limit, of the first collision-time and first collision-location related to a pair of self-stabilizing diffusions and of their related particle approximations. These…

Probability · Mathematics 2022-06-13 Jean-Francois Jabir , Julian Tugaut

We study the existence of a unique solution to semilinear fractional backward doubly stochastic differential equation driven by a Brownian motion and a fractional Brownian motion with Hurst parameter less than 1/2. Here the stochastic…

Probability · Mathematics 2010-05-13 Shuai Jing , Jorge León

In this paper, our main aim is to investigate the strong convergence for a neutral McKean-Vlasov stochastic differential equation with super-linear delay driven by fractional Brownian motion with Hurst exponent $H\in(1/2, 1)$. After giving…

Numerical Analysis · Mathematics 2024-10-01 Shengrong Wang , Jie Xie , Li Tan

In this paper we study the Large Deviation Principle (LDP in abbreviation) for a class of Stochastic Partial Differential Equations (SPDEs) in the whole space $\mathbb{R}^d$, with arbitrary dimension $d\geq 1$, under random influence which…

Probability · Mathematics 2015-05-20 Tarik El Mellali , Mohamed Mellouk

In this paper, we study well-posedness of random periodic solutions of stochastic differential equations (SDEs) of McKean-Vlasov type driven by a two-sided Brownian motion, where the random periodic behaviour is characterised by the…

Probability · Mathematics 2024-12-05 Jianhai Bao , Goncalo Dos Reis , Yue Wu

In this paper, we establish a large deviation principle for a fully non-linear stochastic evolution equation driven by both Brownian motions and Poisson random measures on a given Hilbert space $H$. The weak convergence method plays an…

Probability · Mathematics 2012-11-05 Xue Yang , Jianliang Zhai , Tusheng Zhang

We study the problem of lateral diffusion on a static, quasi-planar surface generated by a stationary, ergodic random field possessing rapid small-scale spatial fluctuations. The aim is to study the effective behaviour of a particle…

Probability · Mathematics 2014-02-03 A. B. Duncan

In this paper, we study the asymptotic behavior of a semi-linear slow-fast stochastic partial differential equation with singular coefficients. Using the Poisson equation in Hilbert space, we first establish the strong convergence in the…

Probability · Mathematics 2021-06-09 Michael Röckner , Longjie Xie , Li Yang

This work considers a type of slow-fast system, where the slow component is driven by fractional Brownian motion with H > 1/2 and the fast component is a Markovian stationary process. Our solution mapping is defined based on the…

Probability · Mathematics 2026-04-29 Xiaoyu Yang , Yong Xu

We consider the asymptotic behaviour of the fluctuation process for large stochastic systems of interacting particles driven by both idiosyncratic and common noise with an interaction kernel \(k \in L^2(\R^d) \cap L^\infty(\R^d)\). Our…

Probability · Mathematics 2026-05-28 Paul Nikolaev

In this paper, we study a class of dissipative stochastic differential equations driven by nonlinear multiplicative fractional Brownian noise with Hurst index $H \in \left(\frac{1}{3},\frac{1}{2})\cup(\frac{1}{2}, 1\right) $. We establish…

Probability · Mathematics 2025-10-02 Qiyong Cao , Hongjun Gao , Wei Wei

In this paper we are concerned with distribution dependent backward stochastic differential equations (DDBSDEs) driven by Gaussian processes. We first show the existence and uniqueness of solutions to this type of equations. This is done by…

Probability · Mathematics 2023-02-08 Xiliang Fan , Jiang-Lun Wu
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