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We prove the transportation inequality with the uniform norm for the laws of diffusion processes with Lipschitz and/or dissipative coefficients and apply them to some singular stochastic differential equations of interest.

Probability · Mathematics 2010-11-05 Ali Suleyman Ustunel

In this paper, we established quadratic transportation cost inequalities for solutions of stochastic reaction diffusion equations driven by multiplicative space-time white noise on the whole line $\mathbb{R}$. Since the space variable is…

Probability · Mathematics 2025-02-12 Yue Li , Shijie Shang , Tusheng Zhang

In this paper, we established a quadratic transportation cost inequality for solutions of stochastic reaction diffusion equations driven by multiplicative space-time white noise based on a new inequality we proved for the moments (under the…

Probability · Mathematics 2019-05-01 Shijie Shang , Tusheng Zhang

We prove transportation-cost inequalities for the law of SDE solutions driven by general Gaussian processes. Examples include the fractional Brownian motion, but also more general processes like bifractional Brownian motion. In case of…

Probability · Mathematics 2016-09-22 Sebastian Riedel

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

We first give a characterization of the L^1-transportation cost-information inequality on a metric space and next find some appropriate sufficient condition to transportation cost-information inequalities for dependent sequences.…

Probability · Mathematics 2007-05-23 H. Djellout , A. Guillin , L. Wu

This article assesses the distance between the laws of stochastic differential equations with multiplicative L\'evy noise on path space in terms of their characteristics. The notion of transportation distance on the set of L\'evy kernels…

Probability · Mathematics 2015-11-25 Jan Gairing , Michael Högele , Tetiana Kosenkova

By using a split argument due to [1], the transportation cost inequality is established on the free path space of Markov processes. The general result is applied to stochastic reaction diffusion equations with random initial values.

Probability · Mathematics 2019-06-19 Feng-Yu Wang , Tusheng Zhang

We establish transportation cost inequalities, with respect to the uniform and $L_2$-metric, on the path space of continuous functions, for laws of solutions of stochastic differential equations with reflections. We also consider the case…

Probability · Mathematics 2019-05-06 Brahim Boufoussi , Soufiane Mouchtabih

We consider stochastic systems involving general -- non-Gaussian and asymmetric -- stable processes. The random quantities, either a stochastic force or a waiting time in a random walk process, explicitly depend on the position. A…

Statistical Mechanics · Physics 2015-06-18 Tomasz Srokowski

Let $L=\DD+Z$ for a $C^1$ vector field $Z$ on a complete Riemannian manifold possibly with a boundary. By using the uniform distance, a number of transportation-cost inequalities on the path space for the (reflecting) $L$-diffusion process…

Probability · Mathematics 2009-08-21 Feng-Yu Wang

We consider a transport-diffusion equation with L\'{e}vy noises and H\"{o}lder continuous coefficients. By using the heat kernel estimates, we derive the Schauder estimates for the mild solutions. Moreover, when the transport term vanishes…

Probability · Mathematics 2017-04-20 Jinlong Wei , Jinqiao Duan , Guangying Lv

We prove that the laws of the BPHZ random models satisfy some transportation cost inequalities in the full subcritical regime if there is no 'variance blowup' and the law of the noise is translation invariant and satisfies some…

Probability · Mathematics 2026-03-27 I. Bailleul , M. Hoshino , R. Takano

We study stochastic differential equations(SDEs) with a small perturbation parameter. Under the dissipative condition on the drift coefficient and the local Lipschitz condition on the drift and diffusion coefficients we prove the existence…

Probability · Mathematics 2022-05-05 Luca Di Persio , Yuri Kondratiev , Viktorya Vardanyan

We discuss transportation cost inequalities for uniform measures on convex bodies, and connections with other geometric and functional inequalities. In particular, we show how transportation inequalities can be applied to the slicing…

Metric Geometry · Mathematics 2008-02-08 Mark W. Meckes

We continue our investigation on the transportation-information inequalities $W_pI$ for a symmetric markov process, introduced and studied in \cite{GLWY}. We prove that $W_pI$ implies the usual transportation inequalities $W_pH$, then the…

Probability · Mathematics 2009-02-13 Arnaud Guillin , Christian Leonard , Feng-Yu Wang , Liming Wu

We establish a quadratic transportation cost inequality under the uniform norm for solutions to mean reflected stochastic partial differential equations, a new type of equation in which the compensating reflection part depends not on the…

Probability · Mathematics 2026-05-19 Beibei Zhang , Bin Qian

In this paper, we prove a Talagrand's T2 transportation cost-information inequality for the law of a stochastic wave equation in spatial dimension d=3 driven by the Gaussian random field, white in time and correlated in space, on the…

Probability · Mathematics 2019-01-25 Yumeng Li , Xinyu Wang

We consider spatially extended conductance based neuronal models with noise described by a stochastic reaction diffusion equation with additive noise coupled to a control variable with multiplicative noise but no diffusion. We only assume a…

Probability · Mathematics 2020-01-16 Martin Sauer , Wilhelm Stannat

This work considers weak approximations of stochastic partial differential equations (SPDEs) driven by L\'evy noise. The SPDEs at hand are parabolic with additive noise processes. A weak-convergence rate for the corresponding Galerkin…

Probability · Mathematics 2016-03-09 Tobias Stüwe , Andrea Barth
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