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Motivated by problems from statistical analysis for discretely sampled SPDEs, first we derive central limit theorems for higher order finite differences applied to stochastic process with arbitrary finitely regular paths. These results are…

Probability · Mathematics 2021-03-09 Igor Cialenco , Hyun-Jung Kim , Gregor Pasemann

We revisit aspects of dynamics and stability of localized states in the deterministic and stochastic discrete nonlinear Schr\"odinger equation. By a combination of analytic and numerical techniques, we show that localized initial conditions…

Pattern Formation and Solitons · Physics 2025-07-24 Mahdieh Ebrahimi , Barbara Drossel , Wolfram Just

Our investigation is specially motivated by the stochastic version of a common model of potential spread in a dendritic tree. We do not assume the noise in the junction points to be Markovian. In fact, we allow for long-range dependence in…

Probability · Mathematics 2018-12-21 Stefano Bonaccorsi , Delio Mugnolo

We consider a stochastic partial differential equation with a logarithmic nonlinearity with singularities at $1$ and $-1$ and a constraint of conservation of the space average. The equation, driven by a trace-class space-time noise,…

Probability · Mathematics 2019-10-21 Ludovic Goudenège , Luigi Manca

We prove pathwise uniqueness for a class of stochastic differential equations (SDE) on a Hilbert space with cylindrical Wiener noise, whose nonlinear drift parts are sums of the sub-differential of a convex function and a bounded part. This…

Probability · Mathematics 2016-06-28 G. Da Prato , F. Flandoli , M. Röckner , A. Yu. Veretennikov

We study singular limits of stochastic evolution equations in the interplay of disappearing strength of the noise and insufficient regularity, where the equation in the limit with noise would not be defined due to lack of regularity. We…

Probability · Mathematics 2023-11-07 Dirk Blömker , Jonas M. Tölle

We consider obstacle problems for nonlinear stochastic evolution equations. More precisely, the leading operator in our equation is a nonlinear, second order pseudomonotone operator of Leray-Lions type. The multiplicative noise term is…

Probability · Mathematics 2025-07-17 Niklas Sapountzoglou , Yassine Tahraoui , Guy Vallet , Aleksandra Zimmermann

We study the small-mass limit, also known as the Smoluchowski-Kramers diffusion approximation (see \cite{kra} and \cite{smolu}), for a system of stochastic damped wave equations, whose solution is constrained to live in the unitary sphere…

Probability · Mathematics 2024-09-13 Sandra Cerrai , Mengzi Xie

We study diffusion processes corresponding to infinite dimensional semilinear stochastic differential equations with local Lipschitz drift term and an arbitrary Lipschitz diffusion coefficient. We prove tightness and the Feller property of…

Analysis of PDEs · Mathematics 2021-05-28 A. Es-Sarhir , M. Scheutzow , J. M. Tölle , O. van Gaans

We investigate a McKean-Vlasov stochastic differential equation with an additive common noise and in which the interaction is through the conditional expectation. We show that, in the presence of an additive individual noise, existence and…

Probability · Mathematics 2026-05-13 Pierre Cardaliaguet , Benjamin Jourdain

We study the validity of a large deviation principle for a class of stochastic nonlinear damped wave equations, of Klein-Gordon type, in the joint small mass and small noise limit. The friction term is assumed to be state dependent.

Probability · Mathematics 2022-08-30 Sandra Cerrai , Mengzi Xie

For the nonlinear stochastic partial differential equation which is driven by multiplicative noise of the form \[D_t^\beta u = \left[ { - {{\left( { - \Delta } \right)}^s}u + \zeta \left( u \right)} \right]dt + A\sum\limits_{m \in Z_0^d}…

Probability · Mathematics 2022-11-18 Fei Gao , Xinyi Xie , Hui Zhan

The aim of this article is to show the global existence of both martingale and pathwise solutions of stochastic equations with a monotone operator, of the Ladyzenskaya-Smagorinsky type, driven by a general Levy noise. The classical approach…

Analysis of PDEs · Mathematics 2021-04-27 Phuong Nguyen , Krutika Tawri , Roger Temam

Motivated by the probabilistic representation for solutions of the Navier-Stokes equations, we introduce a novel class of stochastic differential equations that depend on the entire flow of its time marginals. We establish the existence and…

Probability · Mathematics 2024-12-17 Zimo Hao , Michael Röckner , Xicheng Zhang

We generalize the results of Ambrosio [Invent. Math. 158 (2004), 227--260] on the existence, uniqueness and stability of regular Lagrangian flows of ordinary differential equations to Stratonovich stochastic differential equations with BV…

Probability · Mathematics 2013-04-25 Huaiqian Li , Dejun Luo

This work investigates radial solutions for nonlinear fractional Schr\"odinger equations driven by multiplicative noise. Leveraging radial deterministic and stochastic Strichartz estimates, we establish local well-posedness in the…

Analysis of PDEs · Mathematics 2025-06-03 Ao Zhang , Yanjie Zhang , Jinqiao Duan

This work focuses on the regularization by nonlinear noise for a class of partial differential equations that may only have local solutions. In particular, we obtain the global existence, uniqueness and the Feller property for stochastic 3D…

Probability · Mathematics 2025-07-28 Wei Hong , Shihu Li , Wei Liu

We study the solutions of the stochastic heat equation with multiplicative space-time white noise. We prove a comparison theorem between the solutions of stochastic heat equations with the same noise coefficient which is H\"{o}lder…

Probability · Mathematics 2017-06-14 Leonid Mytnik , Eyal Neuman

We study well-posedness for the stochastic transport equation with transport noise, as introduced by Flandoli, Gubinelli and Priola. We consider periodic solutions in $\rho \in L^{\infty}_{t} L_{x}^{p}$ for divergence-free drifts $u \in…

Probability · Mathematics 2023-07-25 Stefano Modena , Andre Schenke

We present a Bayesian non-parametric way of inferring stochastic differential equations for both regression tasks and continuous-time dynamical modelling. The work has high emphasis on the stochastic part of the differential equation, also…

Machine Learning · Statistics 2020-06-29 Martin Jørgensen , Marc Peter Deisenroth , Hugh Salimbeni