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Distributional properties -including Laplace transforms- of integrals of Markov processes received a lot of attention in the literature. In this paper, we complete existing results in several ways. First, we provide the analytical solution…

Probability · Mathematics 2016-05-09 Frédéric Vrins

We investigate in this work the validity of linear stochastic models for nonlinear dynamical systems. We exploit as our basic tool a previously proposed Rayleigh-Ritz approximation for the effective action of nonlinear dynamical systems…

chao-dyn · Physics 2009-10-31 Gregory L. Eyink

We consider the problem of an overdamped Brownian particle moving in multiscale potential with N + 1 characteristic length scales: the macroscale and N separated microscales. We show that the coarse-grained dynamics is given by an…

Statistical Mechanics · Physics 2016-09-14 A. B. Duncan , S. Kalliadasis , G. A. Pavliotis , M. Pradas

We discuss general multi-dimensional stochastic processes driven by a system of Langevin equations with multiplicative white noise. In particular, we address the problem of how time reversal diffusion processes are affected by the variety…

Statistical Mechanics · Physics 2015-04-14 Miguel Vera Moreno , Zochil González Arenas , Daniel G. Barci

We revise the Levy's construction of Brownian motion as a simple though still rigorous approach to operate with various Gaussian processes. A Brownian path is explicitly constructed as a linear combination of wavelet-based "geometrical…

Statistical Mechanics · Physics 2020-01-03 Denis S. Grebenkov , Dmitry Beliaev , Peter W. Jones

This paper describes a novel numerical approach to find the statistics of the non-stationary response of scalar non-linear systems excited by L\'evy white noises. The proposed numerical procedure relies on the introduction of an integral…

Statistical Mechanics · Physics 2011-08-09 Giulio Cottone

In this paper, a large deviation principle for the strong solution of the p-Laplace equation on unbounded domain driven by small multiplicative Brownian noise is established. The weak convergence approach and the localized time increment…

Probability · Mathematics 2024-08-28 Ananta K Majee

This paper considers the state transition of the stochastic Morris-Lecar neuronal model driven by symmetric $\alpha$-stable L\'evy noise. The considered system is bistable: a stable fixed point (resting state) and a stable limit cycle…

Dynamical Systems · Mathematics 2019-06-19 Rui Cai , Yancai Liu , Jinqiao Duan , Almaz Tesfay Abebe

We derive the path-integral representation of the fractional Ornstein-Uhlenbeck process driven by Riemann-Liouville fractional Gaussian noise, for both the subdiffusive and superdiffusive regimes. We express the corresponding action, which…

Statistical Mechanics · Physics 2025-12-02 Bing Miao , Gleb Oshanin , Luca Peliti

We consider the orthogonalisation of the signature of a stochastic process as the analogue of orthogonal polynomials on path-space. Under an infinite radius of convergence assumption, we prove density of linear functions on the signature in…

Probability · Mathematics 2026-02-24 Ilya Chevyrev , Emilio Ferrucci , Darrick Lee , Terry Lyons , Harald Oberhauser , Nikolas Tapia

We consider a stochastic model of incompressible non-Newtonian fluids of second grade on a bounded domain of $\mathbb{R}^2$ driven by L\'evy noise. Applying the variational approach, global existence and uniqueness of strong probabilistic…

Probability · Mathematics 2017-01-03 Shijie Shang , Jianliang Zhai , Tusheng Zhang

We develop an information-theoretic formulation of stochastic dynamics in which the fundamental stochastic variable is the total action connecting spacetime points, rather than individual paths. By maximizing Shannon entropy over a joint…

The main tool for stochastic calculus with respect to a multidimensional process $B$ with small H\"older regularity index is rough path theory. Once $B$ has been lifted to a rough path, a stochastic calculus -- as well as solutions to…

Probability · Mathematics 2009-06-09 Jeremie Unterberger

We consider stochastic differential equations dY=V(Y)dX driven by a multidimensional Gaussian process X in the rough path sense. Using Malliavin Calculus we show that Y(t) admits a density for t in (0,T] provided (i) the vector fields…

Probability · Mathematics 2007-08-29 Thomas Cass , Peter Friz

A Boussinesq model for the Benard convection under random influences is considered as a system of stochastic partial differential equations. This is a coupled system of stochastic Navier-Stokes equations and the transport equation for…

Probability · Mathematics 2009-05-12 Jinqiao Duan , Annie Millet

In this paper we derive a representation of the deterministic 3-dimensional Navier-Stokes equations based on stochastic Lagrangian paths. The particle trajectories obey SDEs driven by a uniform Wiener process; the inviscid Weber formula for…

Probability · Mathematics 2010-03-16 Peter Constantin , Gautam Iyer

In this article, we consider slow-fast McKean-Vlasov stochastic differential equations driven by Brownian motions and fractional Brownian motions. We give a definition of the large deviation principle (LDP) on the product space related to…

Probability · Mathematics 2023-07-04 Hao Wu , Junhao Hu , Chenggui Yuan

The paper is concerned with the existence and uniqueness of a strong solution to a two-dimensional backward stochastic Navier-Stokes equation with nonlinear forcing, driven by a Brownian motion. We use the spectral approximation and the…

Probability · Mathematics 2011-05-02 Jinniao Qiu , Shanjian Tang , Yuncheng You

This paper derives the non-analytic solution to the Fokker-Planck equation of fractional Brownian motion using the method of Laplace transform. Sequentially, by considering the fundamental solution of the non-analytic solution, this paper…

Analysis of PDEs · Mathematics 2017-04-04 Visant Ahuja

We consider the problem of obtaining effective representations for the solutions of linear, vector-valued stochastic differential equations (SDEs) driven by non-Gaussian pure-jump L\'evy processes, and we show how such representations lead…

Probability · Mathematics 2023-11-09 Marcos Tapia Costa , Ioannis Kontoyiannis , Simon Godsill
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