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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

We study a stochastic Landau-Lifshitz equation on a bounded interval and with finite dimensional noise. We first show that there exists a pathwise unique solution to this equation and that this solution enjoys the maximal regularity…

Probability · Mathematics 2016-09-15 Z. Brzeźniak , B. Goldys , T. Jegaraj

In this paper, we establish the large deviation principle for 3D stochastic primitive equations with small perturbation multiplicative noise. The proof is mainly based on the weak convergence approach.

Probability · Mathematics 2016-06-14 Zhao Dong , Jianliang Zhai , Rangrang Zhang

We study small noise large deviation asymptotics for stochastic differential equations with a multiplicative noise given as a fractional Brownian motion $B^H$ with Hurst parameter $H>\frac12$. The solutions of the stochastic differential…

Probability · Mathematics 2020-06-18 Amarjit Budhiraja , Xiaoming Song

We prove the large deviations principle (LDP) for the law of the solutions to a class of semilinear stochastic partial differential equations driven by multiplicative noise. Our proof is based on the weak convergence approach and…

Probability · Mathematics 2016-07-05 Mohammud Foondun , Leila Setayeshgar

This paper is devoted to investigating the Freidlin-Wentzell's large deviation principle for a class of McKean-Vlasov quasilinear SPDEs perturbed by small multiplicative noise. We adopt the variational framework and the modified weak…

Probability · Mathematics 2021-06-29 Wei Hong , Shihu Li , Wei Liu

In this paper, we establish a large deviation principle for a fully non-linear stochastic evolution equation driven by both Brownian motions and Poisson random measures on a given Hilbert space $H$. The weak convergence method plays an…

Probability · Mathematics 2012-11-05 Xue Yang , Jianliang Zhai , Tusheng Zhang

We investigate a stochastic transport equation driven by a multiplicative noise. For $L^q(0,T;W^{1,p}({\mathbb R}^d;{\mathbb R}^d))$ drift coefficient and $W^{1,r}({\mathbb R}^d)$ initial data, we obtain the existence and uniqueness of…

Analysis of PDEs · Mathematics 2017-11-15 Jinlong Wei , Jinqiao Duan , Hongjun Gao , Guangying Lv

In this paper we consider the stochastic primitive equation for geophysical flows subject to transport noise and turbulent pressure. Admitting very rough noise terms, the global existence and uniqueness of solutions to this stochastic…

Analysis of PDEs · Mathematics 2022-10-26 Antonio Agresti , Matthias Hieber , Amru Hussein , Martin Saal

In this paper, we establish a large deviation principle for stochastic evolution equations with reflection in an infinite dimensional ball. Weak convergence approach plays an important role.

Probability · Mathematics 2024-03-05 Zdzisław Brzeźniak , Qi Li , Tusheng Zhang

In this paper, we prove the existence and uniqueness of solutions of the fractional p-Laplace equation with a polynomial drift of arbitrary order driven by superlinear transport noise. By the monotone argument, we first prove the existence…

Probability · Mathematics 2025-08-21 Bixiang Wang

The Langevin equation with multiplicative noise and state-dependent transport coefficient has to be always complemented with the proper interpretation rule of the noise, such as the Ito and Stratonovich conventions. Although the…

Statistical Mechanics · Physics 2013-12-05 Takeshi Kuroiwa , Kunimasa Miyazaki

We consider a stochastic Cahn-Hilliard partial differential equation driven by a space-time white noise. We prove the Large Deviations Principle (LDP) for the law of the solutions in the H\"older norm. We use the weak convergence approach…

Probability · Mathematics 2017-08-29 Lahcen Boulanba , Mohamed Mellouk

The large deviations analysis of solutions to stochastic differential equations and related processes is often based on approximation. The construction and justification of the approximations can be onerous, especially in the case where the…

Probability · Mathematics 2008-08-28 Amarjit Budhiraja , Paul Dupuis , Vasileios Maroulas

We study a class of linear first and second order partial differential equations driven by weak geometric $p$-rough paths, and prove the existence of a unique solution for these equations. This solution depends continuously on the driving…

Analysis of PDEs · Mathematics 2008-03-24 Michael Caruana , Peter Friz

We investigate the pathwise well-posedness of stochastic evolution equations perturbed by multiplicative Neumann boundary noise, such as fractional Brownian motion for $H\in(1/3,1/2]$. Combining the controlled rough path approach with the…

Probability · Mathematics 2023-10-17 Alexandra Neamtu , Tim Seitz

In this paper, we established a quadratic transportation cost inequality for scalar stochastic conservation laws driven by multiplicative noise. The doubling variables method plays an important role.

Probability · Mathematics 2021-01-01 Rangrang Zhang , Tusheng Zhang

We establish a large deviation principle (LDP) for a class of stochastic porous media equations driven by L\'{e}vy-type noise on a $\sigma$-finite measure space $(E,\mathcal{B}(E),\mu)$, with the Laplacian replaced by a negative definite…

Probability · Mathematics 2023-12-07 Weina Wu , Jianliang Zhai

In this paper, we establish a large deviation principle for the stochastic generalized Ginzburg-Landau equation driven by jump noise. The main difficulties come from the highly non-linear coefficient. Here we adopt a new sufficient…

Probability · Mathematics 2021-11-17 Ran Wang , Beibei Zhang

We study the stochastic transport equation with globally $\beta$-H\"older continuous and bounded vector field driven by a non-degenerate pure-jump L\'evy noise of $\alpha$-stable type. Whereas the deterministic transport equation may lack…

Probability · Mathematics 2025-12-22 Zdzisław Brzeźniak , Enrico Priola , Jianliang Zhai , Jiahui Zhu