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Related papers: Limit theorems of SDEs driven by L\'evy processes …

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Semilinear hyperbolic stochastic partial differential equations (SPDEs) find widespread applications in the natural and engineering sciences. However, the traditional Gaussian setting may prove too restrictive, as phenomena in mathematical…

Numerical Analysis · Mathematics 2023-07-04 Andrea Barth , Andreas Stein

In this article, we study the effects of the propagation of a non-degenerate L\'evy noise through a chain of deterministic differential equations whose coefficients are H\"older continuous and satisfy a weak H\"ormander-like condition. In…

Analysis of PDEs · Mathematics 2023-03-27 L. Marino , S. Menozzi

We characterise the convergence of a certain class of discrete time Markov processes toward locally Feller processes in terms of convergence of associated operators. The theory of locally Feller processes is applied to L\'evy-type processes…

Probability · Mathematics 2017-09-12 Mihai Gradinaru , Tristan Haugomat

We show the existence of L\'evy-type stochastic processes in one space dimension with characteristic triplets that are either discontinuous at thresholds, or are stable-like with stability index functions for which the closures of the…

Probability · Mathematics 2012-08-09 Peter Imkeller , Niklas Willrich

In this paper, we consider stochastic differential equations whose drift coefficient is superlinearly growing and piece-wise continuous, and whose diffusion coefficient is superlinearly growing and locally H\"older continuous. We first…

Probability · Mathematics 2023-05-15 Minh-Thang Do , Hoang-Long Ngo , Nhat-An Pho

We introduce a new class of numerical methods for solving McKean-Vlasov stochastic differential equations, which are relevant in the context of distribution-dependent or mean-field models, under super-linear growth conditions for both the…

Numerical Analysis · Mathematics 2025-02-10 Jiamin Jian , Qingshuo Song , Xiaojie Wang , Zhongqiang Zhang , Yuying Zhao

In this paper, we study almost periodic solutions for semilinear stochastic differential equations driven by L\'{e}vy noise with exponential dichotomy property. Under suitable conditions on the coefficients, we obtain the existence and…

Probability · Mathematics 2014-04-29 Yan Wang

We study the existence, uniqueness and approximation of solutions of stochastic differential equations with constraints driven by processes with bounded p-variation. Our main tool are new estimates showing Lipschitz continuity of the…

Probability · Mathematics 2015-05-07 Adrian Falkowski , Leszek Slominski

The strong convergence of the semi-implicit Euler-Maruyama (EM) method for stochastic differential equations with non-linear coefficients driven by a class of L\'evy processes is investigated. The dependence of the convergence order of the…

Numerical Analysis · Mathematics 2023-11-21 Xiaotong Li , Wei Liu , Hongjiong Tian

The convergence of stochastic interacting particle systems in the mean-field limit to solutions of conservative stochastic partial differential equations is established, with optimal rate of convergence. As a second main result, a…

Probability · Mathematics 2022-12-15 Benjamin Gess , Rishabh S. Gvalani , Vitalii Konarovskyi

In this article we prove the pathwise uniqueness for stochastic differential equations in $\mR^d$ with time-dependent Sobolev drifts, and driven by symmetric $\alpha$-stable processes provided that $\alpha\in(1,2)$ and its spectral measure…

Probability · Mathematics 2011-01-17 Xicheng Zhang

We connect boundary conditions for one-sided pseudo-differential operators with the generators of modified one-sided L\'evy processes. On one hand this allows modellers to use appropriate boundary conditions with confidence when restricting…

Probability · Mathematics 2021-03-02 Boris Baeumer , Mihály Kovács , Lorenzo Toniazzi

In this paper, we consider a nonlinear filtering model with observations driven by correlated Wiener processes and point processes. We first derive a Zakai equation whose solution is a unnormalized probability density function of the filter…

Numerical Analysis · Mathematics 2022-11-29 Fengshan Zhang , Yongkui Zou , Shimin Chai , Yanzhao Cao

We connect boundary conditions for one-sided pseudo-differential operators with the generators of modified one-sided L\'evy processes. On one hand this allows modellers to use appropriate boundary conditions with confidence when restricting…

Probability · Mathematics 2020-12-22 Boris Baeumer , Mihály Kovács , Lorenzo Toniazzi

We prove the well-posedness of solutions to McKean-Vlasov stochastic differential equations driven by L\'evy noise under mild assumptions where, in particular, the L\'evy measure is not required to be finite. The drift, diffusion and jump…

Probability · Mathematics 2020-10-20 Neelima , Sani Biswas , Chaman Kumar , Gonçalo dos Reis , Christoph Reisinger

In this paper, we deal with a class of reflected backward stochastic differential equations associated to the subdifferential operator of a lower semi-continuous convex function driven by Teugels martingales associated with L\'{e}vy…

Probability · Mathematics 2015-05-13 Yong Ren , Xiliang Fan

We investigate three types of averaging principles and the normal deviation for multi-scale stochastic differential equations (in short, SDEs) with polynomial nonlinearity. More specifically, we first demonstrate the strong convergence of…

Dynamical Systems · Mathematics 2023-08-22 Mengyu Cheng , Zhenxin Liu , Michael Röckner

``Orderly divergence'' deals with limit theorems for weighted stochastic Gamma integrals of otherwise nonintegrable functions. Although for monotonic functions this category usually coincides with the classical notion of weighted limit…

Probability · Mathematics 2024-06-03 Jerzy Szulga

We present a novel idea for a coupling of solutions of stochastic differential equations driven by L\'{e}vy noise, inspired by some results from the optimal transportation theory. Then we use this coupling to obtain exponential…

Probability · Mathematics 2017-05-02 Mateusz B. Majka

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
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