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In this paper we investigate a non-linear and non-local one dimensional transport equation under random perturbations on the real line. We first establish a local-in-time theory, i.e., existence, uniqueness and blow-up criterion for…

Analysis of PDEs · Mathematics 2022-03-23 Diego Alonso-Orán , Yingting Miao , Hao Tang

We introduce an extended variational framework for nonlinear SPDEs with unbounded noise, defining three different solution types of increasing strength along with criteria to establish their existence. The three notions can be understood as…

Analysis of PDEs · Mathematics 2024-06-28 Daniel Goodair

We construct H\"older continuous, global-in-time probabilistically strong solutions to 3D Euler equations perturbed by Stratonovich transport noise. Kinetic energy of the solutions can be prescribed a priori up to a stopping time, that can…

Probability · Mathematics 2023-10-05 Martina Hofmanová , Theresa Lange , Umberto Pappalettera

The Voigt regularization is a technique used to model turbulent flows, offering advantages such as sharing steady states with the Navier-Stokes equations and requiring no modification of boundary conditions; however, the parabolic…

Analysis of PDEs · Mathematics 2024-11-01 Zdzislaw Brzeźniak , Adam Larios , Isabel Safarik

In this paper, we consider the 2D stochastic Nernst-Planck-Navier-Stokes equations with transport noise. By assuming the ionic species have the same diffusivity and opposite valences, we prove the global well-posedness of the system.…

Analysis of PDEs · Mathematics 2024-01-23 Quyuan Lin , Rongchang Liu , Weinan Wang

We consider the 2D stochastic Navier-Stokes equations driven by noise that has the regularity of space-time white noise but doesn't exactly coincide with it. We show that, provided that the intensity of the noise is sufficiently weak at…

Probability · Mathematics 2025-10-22 Martin Hairer , Wenhao Zhao

In this paper, we prove the global well-posedness and interior regularity for the 2D Navier-Stokes equations driven by a fractional noise acting as an inhomogeneous Dirichlet-type boundary condition. The model describes a vertical slice of…

Analysis of PDEs · Mathematics 2025-06-17 Antonio Agresti , Alexandra Blessing , Eliseo Luongo

Finite element simulations have been used to solve various partial differential equations (PDEs) that model physical, chemical, and biological phenomena. The resulting discretized solutions to PDEs often do not satisfy requisite physical…

Numerical Analysis · Mathematics 2022-03-17 Vidhi Zala , Robert M. Kirby , Akil Narayan

For the $3D$ fractional Navier--Stokes equations perturbed by transport noise, we prove the existence of infinitely many H\"older continuous analytically weak, probabilistically strong Leray--Hopf solutions starting from the same…

Analysis of PDEs · Mathematics 2024-12-24 Theresa Lange , Marco Rehmeier , Andre Schenke

We address the global existence of solutions to the stochastic Navier-Stokes equations with multiplicative noise and with initial data in $H^{1/2}(\mathbb{T}^{3})$. We prove that the solution exists globally in time with probability…

Probability · Mathematics 2025-01-20 Mustafa Sencer Aydın , Igor Kukavica , Fanhui Xu

The aim of this work is to prove an existence and uniqueness result of Kato-Fujita type for the Navier-Stokes equations, in vorticity form, in $2-D$ and $3-D$, perturbed by a gradient type multiplicative Gaussian noise (for sufficiently…

Analysis of PDEs · Mathematics 2019-05-08 Ionut Munteanu , Michael Roeckner

In this paper we study a non strictly systems of conservation law by stochastic perturbation. We show the existence and uniqueness of the solution. We do not assume that $BV$-regularity for the initial conditions. The proofs are based on…

Analysis of PDEs · Mathematics 2017-10-04 Christian Olivera

In this paper we treat semilinear stochastic partial differential equations by two methods. First, we extend the framework of [BDR10] from a Hilbert space to a Gelfand triple and as an application we prove the existence of solutions for the…

Probability · Mathematics 2014-02-05 Michael Röckner , Rongchan Zhu , Xiangchan Zhu

A system of partial differential equations representing stochastic neural fields was recently proposed with the aim of modelling the activity of noisy grid cells when a mammal travels through physical space. The system was rigorously…

Analysis of PDEs · Mathematics 2023-07-18 José Antonio Carrillo , Pierre Roux , Susanne Solem

We consider the numerical approximation of a general second order semi--linear parabolic stochastic partial differential equation (SPDE) driven by additive space-time noise. We introduce a new modified scheme using a linear functional of…

Numerical Analysis · Mathematics 2016-07-20 Gabriel J Lord , Antoine Tambue

We investigate the behavior of integral formulations of variable coefficient elliptic partial differential equations (PDEs) in the presence of steep internal layers. In one dimension, the equations that arise can be solved analytically and…

Numerical Analysis · Mathematics 2013-05-31 Travis Askham , Leslie Greengard

Starting from the simple point process model of 1/f noise we derive a stochastic nonlinear differential equation for the signal exhibiting 1/f noise in any desirably wide range of frequency. A stochastic differential equation (the general…

Statistical Mechanics · Physics 2009-11-10 B. Kaulakys , J. Ruseckas

We consider the stationary (time-independent) Navier-Stokes equations in the whole threedimensional space, under the action of a source term and with the fractional Laplacian operator (--$\Delta$) $\alpha$/2 in the diffusion term. In the…

Analysis of PDEs · Mathematics 2024-05-16 Oscar Jarrín , Gastón Vergara-Hermosilla

In this paper, we study the regularities of solutions of nonlinear stochastic partial differential equations in the framework of Hilbert scales. Then we apply our general result to several typical nonlinear SPDEs such as stochastic Burgers…

Probability · Mathematics 2008-01-28 Xicheng Zhang

We develop a framework for estimating unknown partial differential equations from noisy data, using a deep learning approach. Given noisy samples of a solution to an unknown PDE, our method interpolates the samples using a neural network,…

Machine Learning · Computer Science 2019-10-24 Ali Hasan , João M. Pereira , Robert Ravier , Sina Farsiu , Vahid Tarokh
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