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We consider a diffusion process in $\mathbb{R}^d$ with a generator of the form $ L:=\frac 12 e^{V(x)}div(e^{-V(x)}\nabla ) $ where $V$ is measurable and periodic. We only assume that $e^V$ and $e^{-V}$ are locally integrable. We then show…

Probability · Mathematics 2016-01-13 Moustapha Ba , Pierre Mathieu

In this paper, we generalize the weighted Fourier transform with respect to a function, originally proposed for the one-dimensional case in \cite{Dorrego}, to the $n$-dimensional Euclidean space $\mathbb{R}^{n}$. We develop a comprehensive…

Classical Analysis and ODEs · Mathematics 2025-12-12 Gustavo Dorrego , Luciano Luque

Let ${\psi}:\mathbb{R}^{+}\rightarrow\mathbb{R}^{+}$ be a smooth and continuous real function and $\psi\in\mathrm{L}^{2}(\mathbb{R}^{+})$. Let ${B}(t)$ be a standard Brownian motion defined with respect to a probability space…

Probability · Mathematics 2023-02-08 Steven D Miller

For continuous \gamma, g:[0,1]\to(0,\infty), consider the degenerate stochastic differential equation dX_t=[1-|X_t|^2]^{1/2}\gamma(|X_t|) dB_t-g(|X_t|)X_t dt in the closed unit ball of R^n. We introduce a new idea to show pathwise…

Probability · Mathematics 2007-05-23 Dante DeBlassie

In this paper we construct a theory of stochastic integration of processes with values in $\mathcal{L}(H,E)$, where $H$ is a separable Hilbert space and $E$ is a UMD Banach space (i.e., a space in which martingale differences are…

Probability · Mathematics 2007-08-22 J. M. A. M. van Neerven , M. C. Veraar , L. Weis

In this paper we explore the fundamentals of the Martingale Representation Theorem (MRT) and a closely related result, the Clark-Ocone formula. We also investigate how far these theorems can be taken, notably beyond the regular Sobolev…

Probability · Mathematics 2013-06-25 Deborah Schneider-Luftman

The $L^p$ maximal inequalities for martingales are one of the classical results in the theory of stochastic processes. Here we establish the sharp moderate maximal inequalities for one-dimensional diffusion processes, which include the…

Probability · Mathematics 2021-11-05 Xian Chen , Yong Chen , Mumien Cheng , Chen Jia

We introduce a novel concept of dissipative measure-valued martingale solution to the stochastic Euler equations describing the motion of an inviscid incompressible fluid. These solutions are characterized by a parametrized Young measure…

Analysis of PDEs · Mathematics 2020-12-21 Abhishek Chaudhary , Ujjwal Koley

In this paper we consider parameter estimation for discretely observed diffusion processes. In particular, we focus on data that are observed at low frequency and methodology that can estimate parameters with uncertainty quantification.…

Computation · Statistics 2026-05-01 Jingning Yao , Ajay Jasra , Sheng Jiang

We discuss a family of time-inhomogeneous two-dimensional diffusions, defined over a finite time interval $[0,T]$, having transition density functions that are expressible in terms of the integral kernels for negative exponentials of the…

Probability · Mathematics 2023-07-04 Jeremy Clark , Barkat Mian

This paper studies small-time behavior at the supremum of a diffusion process. For a solution to the SDE $\mathrm{d} X_t=\mu(X_t)\mathrm{d} t+\sigma(X_t)\mathrm{d} W_t$ (where $W$ is a standard Brownian motion) we consider…

Probability · Mathematics 2021-11-18 Jakob Dalsgaard Thøstesen

We consider one-dimensional diffusions, with polynomial drift and diffusion coefficients, so that in particular the motion can be space-inhomogeneous, interacting via one-sided reflections. The prototypical example is the well-known model…

Probability · Mathematics 2023-07-05 Theodoros Assiotis

This article studies the quasi-stationary behaviour of absorbed one-dimensional diffusions. We obtain necessary and sufficient conditions for the exponential convergence to a unique quasi-stationary distribution in total variation,…

Probability · Mathematics 2017-03-03 Nicolas Champagnat , Denis Villemonais

We formulate and solve the martingale problem in a nonlinear expectation space. Unlike the classical work of Stroock and Varadhan (1969) where the linear operator in the associated PDE is naturally defined from the corresponding diffusion…

Probability · Mathematics 2014-04-01 Xin Guo , Chen Pan , Shige Peng

It is known the Girsanov exponent $\mathfrak{z}_t$, being solution of Doleans-Dade equation $ \mathfrak{z_t}=1+\int_0^t\alpha(\omega,s)dB_s $ generated by Brownian motion $B_t$ and a random process $\alpha(\omega,t)$ with…

Probability · Mathematics 2009-12-07 R. Liptser

We consider a stochastic Volterra integral equation with regular path-dependent coefficients and a Brownian motion as integrator in a multidimensional setting. Under an imposed absolute continuity condition, the unique solution is a…

Probability · Mathematics 2021-03-29 Alexander Kalinin

Extending previous work [arXiv:1408.0628] by the first author we present a variant of the Arratia flow, which consists of a collection of coalescing Brownian motions starting from every point of the unit interval. The important new feature…

Probability · Mathematics 2020-10-21 Vitalii Konarovskyi , Max von Renesse

Let $M$ be a $d$-dimensional connected compact Riemannian manifold with boundary $\partial M$, let $V\in C^2(M)$ such that $\mu({\rm d} x):={\rm e}^{V(x)}{\rm d} x$ is a probability measure, and let $X_t$ be the diffusion process generated…

Probability · Mathematics 2022-04-11 Feng-Yu Wang

We solve explicitly the following problem: for a given probability measure mu, we specify a generalised martingale diffusion X which, stopped at an independent exponential time T, is distributed according to mu. The process X is specified…

Probability · Mathematics 2009-12-10 Alexander M. G. Cox , David G. Hobson , Jan K. Obłój

We consider multiple stochastic integrals with respect to c\`adl\`ag martingales, which approximate a cylindrical Wiener process. We define a chaos expansion, analogous to the case of multiple Wiener stochastic integrals, for these…

Probability · Mathematics 2023-07-26 Paolo Grazieschi , Konstantin Matetski , Hendrik Weber
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