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Let $X=\{X(t),t\in R_+\}$ be a real-valued symmetric L\'{e}vy process with continuous local times $\{L^x_t,(t,x)\in R_+\times R\}$ and characteristic function $Ee^{i\lambda X(t)}=e^{-t\psi(\lambda)}$. Let…

Probability · Mathematics 2009-09-29 Michael B. Marcus , Jay Rosen

We construct a series of stochastic differential equations of the form $dX_t = b(t, X_t) dt + dB_t$ which exhibit nonuniqueness in the path-by-path sense while having a unique adapted solution in the sense of stochastic processes, i.e.…

Probability · Mathematics 2020-12-29 Alexander Shaposhnikov , Lukas Wresch

We prove that weakly continuous solutions to martingale problems admit a canonical regular conditional probability distribution. This allows for the construction of time consistent convex dynamic procedures in a non dominated setting.…

Probability · Mathematics 2012-10-09 Jocelyne Bion-Nadal

Poincare's invariance principle for Hamiltonian flows implies Kelvin's principle for solution to Incompressible Euler Equation. Iyer-Constantin Circulation Theorem offers a stochastic analog of Kelvin's principle for Navier-Stokes Equation.…

Probability · Mathematics 2013-11-01 Fraydoun Rezakhanlou

In the present work, we establish the approximation of nonlinear stochastic partial differential equation (SPDE) driven by cylindrical {\alpha}-stable L\'evy processes via modulation or amplitude equations. We study SPDEs with a cubic…

Dynamical Systems · Mathematics 2021-06-30 Shenglan Yuan , Dirk Blömker

We consider flows of ordinary differential equations (ODEs) driven by path differentiable vector fields. Path differentiable functions constitute a proper subclass of Lipschitz functions which admit conservative gradients, a notion of…

Machine Learning · Computer Science 2022-01-12 Swann Marx , Edouard Pauwels

We study the relation between flow structure and fluid deformation in steady two-dimensional random flows. Beyond the linear (shear flow) and exponential (chaotic flow) elongation paradigms, we find a broad spectrum of stretching behaviors,…

Fluid Dynamics · Physics 2016-08-25 Marco Dentz , Daniel R. Lester , Tanguy Le Borgne , Felipe P. J. de Barros

We study the asymptotic convergence of solutions as $t\rightarrow\infty$ of $\partial_t u=-f(u)+\int f(u)$, a nonlocal differential equation that is formally a gradient flow in a constant-mass subspace of $L^2$ arising from simplified…

Classical Analysis and ODEs · Mathematics 2024-09-16 Sangmin Park , Robert L. Pego

We give a new definition of a L\'{e}vy driven CARMA random field, defining it as a generalized solution of a stochastic partial differential equation (SPDE). Furthermore, we give sufficient conditions for the existence of a mild solution of…

Probability · Mathematics 2019-04-08 David Berger

We consider reflected generalized backward doubly stochastic differential equations driven by a non-homogeneous L\'evy process. Under stochastic conditions on the coefficients, we prove the existence and uniqueness of a solution.…

Probability · Mathematics 2026-02-25 Badr Elmansouri , Mohammed Elhachemy , Mohamed Marzougue , Mohamed El Jamali

Using probabilistic methods we study the existence of viscosity solutions to non-linear integro-differential equations $$\partial_t u(t,x) - \sup_{\alpha \in I} \bigg( b_{\alpha}(x) \cdot \nabla_x u(t,x) + \frac{1}{2}…

Probability · Mathematics 2019-06-14 Franziska Kühn

Semilinear stochastic evolution equations with multiplicative L\'evy noise and monotone nonlinear drift are considered. Unlike other similar works, we do not impose coercivity conditions on coefficients. We establish the continuous…

Probability · Mathematics 2014-06-17 Erfan Salavati , Bijan Z. Zangeneh

We obtain sample-path large deviations for a class of one-dimensional stochastic differential equations with bounded drifts and heavy-tailed L\'evy processes. These heavy-tailed L\'evy processes do not satisfy the exponential integrability…

Probability · Mathematics 2023-09-15 Wei Wei , Qiao Huang , Jinqiao Duan

This paper introduces Switching Processes, called SP. Their constructions are inspired by the PDMP's ones (PDMP stands for Piecewise Deterministic Markov Process). A Markov process, called the intrinsic process, replaces the PDMP's flow.…

Probability · Mathematics 2017-01-19 Christiane Cocozza-Thivent

The goal of this paper is to clarify when a semilinear stochastic partial differential equation driven by L\'evy processes admits an affine realization. Our results are accompanied by several examples arising in natural sciences and…

Probability · Mathematics 2025-11-21 Stefan Tappe

We show the pathwise uniqueness for stochastic partial differential equation driven by a cylindrical $\alpha$-stable process with H\"older continuous drift, thus obtaining an infinite dimensional generalization of the result of Priola…

Probability · Mathematics 2017-03-03 Xiaobin Sun , Longjie Xie , Yingchao Xie

We present an investigation of stochastic evolution in which a family of evolution equations in $L^1$ are driven by continuous-time Markov processes. These are examples of so-called piecewise deterministic Markov processes (PDMP's) on the…

Probability · Mathematics 2020-12-01 Paweł Klimasara , Michael C. Mackey , Andrzej Tomski , Marta Tyran-Kamińska

Let $A$ be a pseudo-differential operator with negative definite symbol $q$. In this paper we establish a sufficient condition such that the well-posedness of the $(A,C_c^{\infty}(\mathbb{R}^d))$-martingale problem implies that the unique…

Probability · Mathematics 2018-05-17 Franziska Kühn

For a given differentiable map $(x,y)\to (X(x,y),Y(x,y))$, which has an inverse, we show that there exists a Hamiltonian flow in which x plays the role of the time variable while y is fixed.

Exactly Solvable and Integrable Systems · Physics 2015-06-26 Satoru Saito , Akira Shudo , Jun-ichi Yamamoto , Katsuhiko Yoshida

In this paper, we study weak and strong transience of a class of Feller processes associated with pseudo-differential operators, the so-called L\'evy-type processes. As a main result, we derive Chung-Fuchs type conditions (in terms of the…

Probability · Mathematics 2016-04-14 Nikola Sandrić