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We consider the Navier-Stokes system describing the motion of a compressible barotropic fluid driven by stochastic external forces. Our approach is semi-deterministic, based on solving the system for each fixed representative of the random…

Analysis of PDEs · Mathematics 2012-06-06 Eduard Feireisl , Bohdan Maslowski , Antonin Novotny

Modern generative models can be understood as probability transport from a simple base distribution to a target data distribution. Deterministic transport models offer tractable velocity-field parameterizations, whereas stochastic…

Machine Learning · Computer Science 2026-05-19 Xingyu Song , Yuan Mei , Naoya Takeishi

Many physical systems characterized by nonlinear multiscale interactions can be effectively modeled by treating unresolved degrees of freedom as random fluctuations. However, even when the microscopic governing equations and qualitative…

Statistical Mechanics · Physics 2021-06-07 Jared L. Callaham , Jean-Christophe Loiseau , Georgios Rigas , Steven L. Brunton

We first prove some general results on pathwise uniqueness, comparison property and existence of nonnegative strong solutions of stochastic equations driven by white noises and Poisson random measures. The results are then used to prove the…

Probability · Mathematics 2012-04-12 Donald A. Dawson , Zenghu Li

A paradigm for isothermal, mechanical rectification of stochastic fluctuations is introduced in this paper. The central idea is to transform energy injected by random perturbations into rigid-body rotational kinetic energy. The prototype…

Probability · Mathematics 2007-10-18 Nawaf Bou-Rabee , Houman Owhadi

In this paper we analyze the theoretical properties of a stochastic representation of the incompressible Navier-Stokes equations defined in the framework of the modeling under location uncertainty (LU). This setup built from a stochastic…

Analysis of PDEs · Mathematics 2023-02-01 Arnaud Debussche , Berenger Hug , Etienne Memin

In this paper we study binary interaction schemes with uncertain parameters for a general class of Boltzmann-type equations with applications in classical gas and aggregation dynamics. We consider deterministic (i.e., a priori averaged) and…

Analysis of PDEs · Mathematics 2018-11-05 Andrea Tosin , Mattia Zanella

We study the Navier-Stokes equations governing the motion of isentropic compressible fluid in three dimensions driven by a multiplicative stochastic forcing. In particular, we consider a stochastic perturbation of the system as a function…

Analysis of PDEs · Mathematics 2017-01-03 Dominic Breit , Martina Hofmanová

Geophysical methods provide a cost-effective way to characterize the subsurface for hydrogeological projects, but they rely on solving an inverse problem. Traditionally, deterministic approaches are used, which face challenges due to…

Geophysics · Physics 2025-12-05 Arsalan Ahmed , Thomas Hermans , David Dudal , Wouter Deleersnyder

We develop a general formalism for introducing stochastic fluctuations around thermodynamic equilibrium which takes into account, for the first time, recent developments on the causality and stability properties of relativistic hydrodynamic…

Nuclear Theory · Physics 2023-06-16 Nicki Mullins , Mauricio Hippert , Jorge Noronha

We prove existence of a stochastic flow of diffeomorphisms generated by SDEs with drift in $L^q_t C^{0, \alpha}_x$ for any $q \in [2, \infty)$ and $\alpha \in (0, 1)$. This result is achieved using a Zvonkin-type transformation for the SDE.…

Probability · Mathematics 2025-10-02 Magnus C. Ørke

We develop a Bayesian methodology for numerical solution of the incompressible Navier--Stokes equations with quantified uncertainty. The central idea is to treat discretized Navier--Stokes dynamics as a state-space model and to view…

Computation · Statistics 2026-02-04 Nicholas Polson , Vadim Sokolov

We introduce a stochastic version of Proudman-Taylor model, a 2D-3C fluid approximation of the 3D Navier-Stokes equations, with the small-scale turbulence modeled by a transport-stretching noise. For this model we may rigorously take a…

Probability · Mathematics 2024-06-12 Franco Flandoli , Dejun Luo

A systematic Bayesian framework is developed for physics constrained parameter inference ofstochastic differential equations (SDE) from partial observations. The physical constraints arederived for stochastic climate models but are…

Data Analysis, Statistics and Probability · Physics 2016-11-25 Daniel Peavoy , Christian L. E. Franzke , Gareth O. Roberts

Two different types of perturbations of the Lorenz 63 dynamical system for Rayleigh-Benard convection by multiplicative noise -- called stochastic advection by Lie transport (SALT) noise and fluctuation-dissipation (FD) noise -- are found…

Dynamical Systems · Mathematics 2019-12-20 Bernard J. Geurts , Darryl D. Holm , Erwin Luesink

A stochastic wavevector approach is formulated to accurately represent compressible turbulence subject to rapid deformations. This approach is inspired by the incompressible particle representation model of Kassinos (1995) and preserves the…

Fluid Dynamics · Physics 2025-01-30 Noah Zambrano , Karthik Duraisamy

We are concerned with multidimensional nonlinear stochastic transport equation driven by Brownian motions. For irregular fluxes, by using stochastic BGK approximations and commutator estimates, we gain the existence and uniqueness of…

Probability · Mathematics 2018-01-16 Jinlong Wei , Rongrong Tian , Guangying Lv

Suppose the observations of Lagrangian trajectories for fluid flow in some physical situation can be modelled sufficiently accurately by a spatially correlated It\^o stochastic process (with zero mean) obtained from data which is taken in…

Fluid Dynamics · Physics 2021-03-17 Darryl D. Holm

Fluids can behave in a highly irregular, turbulent way. It has long been realised that, therefore, some weak notion of solution is required when studying the fundamental partial differential equations of fluid dynamics, such as the…

Analysis of PDEs · Mathematics 2023-06-14 Dennis Gallenmüller , Raphael Wagner , Emil Wiedemann

We propose a general formalism, within large deviation theory, giving access to the exact statistics of fluctuations of ballistically transported conserved quantities in homogeneous, stationary states. The formalism is expected to apply to…

Statistical Mechanics · Physics 2020-12-09 Benjamin Doyon , Jason Myers