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In this note, we prove the large deviation principle for the 2D-fractional stochastic Navier-Stokes equation on the torus under the dissipation order $ \alpha \in [\frac43, 2]$.

Probability · Mathematics 2013-09-06 Latifa Debbi

We study the two-dimensional incompressible Navier-Stokes equation on the torus, driven by Gaussian noise that is white in time and colored in space. We consider the case where the magnitude of the random forcing $\sqrt{\e}$ and its…

Probability · Mathematics 2021-01-01 Sandra Cerrai , Nicholas Paskal

We consider stochastic systems of interacting particles or agents, with dynamics determined by an interaction kernel which only depends on pairwise distances. We study the problem of inferring this interaction kernel from observations of…

Statistics Theory · Mathematics 2020-07-31 Fei Lu , Mauro Maggioni , Sui Tang

Large deviation theory offers a powerful and general statistical framework to study the asymptotic dynamical properties of rare events. The application of the formalism to concrete experimental situations is, however, often restricted by…

Statistical Mechanics · Physics 2023-09-13 Maxime Debiossac , Nikolai Kiesel , Eric Lutz

We consider a generic Hamiltonian system of nonlinear interacting waves with 3-wave interactions. In the kinetic regime of wave turbulence, which assumes weak nonlinearity and large system size, the relevant observable associated with the…

Statistical Mechanics · Physics 2022-09-07 Jules Guioth , Freddy Bouchet , Gregory L. Eyink

We prove a large deviation principle for the point process associated to $k$-element connected components in $\mathbb R^d$ with respect to the connectivity radii $r_n\to\infty$. The random points are generated from a homogeneous Poisson…

Probability · Mathematics 2022-10-19 Christian Hirsch , Takashi Owada

We prove a large deviations principle for the empirical measure of the one dimensional symmetric simple exclusion process in contact with reservoirs. The dynamics of the reservoirs is slowed down with respect to the dynamics of the system,…

Probability · Mathematics 2021-07-16 Tertuliano Franco , Patrícia Gonçalves , Adriana Neumann

We establish a large deviation principle for the empirical measure process associated with a general class of finite-state mean field interacting particle systems with Lipschitz continuous transition rates that satisfy a certain ergodicity…

Probability · Mathematics 2016-01-26 Paul Dupuis , Kavita Ramanan , Wei Wu

We establish a large deviation principle for time dependent trajectories (paths) of the empirical density of $N$ particles with long range interactions, for homogeneous systems. This result extends the classical kinetic theory that leads to…

Statistical Mechanics · Physics 2022-01-19 Ouassim Feliachi , Freddy Bouchet

We derive some large deviation bounds for events related to the "true self-repelling motion", a one-dimensional self-interacting process introduced by Toth and Werner, that has very different path properties than usual diffusion processes.…

Probability · Mathematics 2012-07-16 Laure Dumaz

Numerical simulation of stochastic dynamics of vortex filaments under action of random (Langevin) force is fulfilled. Calculations are performed on base of the full Biot--Savart law for different intensities of the Langevin force. A new…

Statistical Mechanics · Physics 2008-10-06 Luiza P. Kondaurova , Sergey K. Nemirovskii

We study a mean field approximation for the 2D Euler vorticity equation driven by a transport noise. We prove that the Euler equations can be approximated by interacting point vortices driven by a regularized Biot-Savart kernel and the same…

Probability · Mathematics 2020-09-25 Michele Coghi , Mario Maurelli

A stochastic description of solutions of the Navier-Stokes equation is investigated. These solutions are represented by laws of finite dimensional semi-martingales and characterized by a weak Euler- Lagrange condition. A least action…

Probability · Mathematics 2016-02-12 Ana Bela Cruzeiro , Rémi Lassalle

A pathwise large deviation result is proved for the pure jump models of $k$-nary interacting particle system introduced by Kolokoltsov that generalize classical Boltzmann's collision model, Smoluchovski's coagulation model and many others.…

Probability · Mathematics 2021-06-09 Wen Sun

We prove a Large Deviations Principle (LDP) for systems of diffusions (particles) interacting through their ranks, when the number of particles tends to infinity. We show that the limiting particle density is given by the unique solution of…

Probability · Mathematics 2017-04-05 Amir Dembo , Mykhaylo Shkolnikov , S. R. Srinivasa Varadhan , Ofer Zeitouni

We have found an infinite dimensional manifold of exact solutions of the Navier-Stokes loop equation for the Wilson loop in decaying Turbulence in arbitrary dimension $d >2$. This solution family is equivalent to a fractal curve in complex…

Fluid Dynamics · Physics 2023-10-26 Alexander Migdal

This paper is devoted to proving the small noise asymptotic behaviour, particularly large deviation principle, for multi-scale stochastic dynamical systems with fully local monotone coefficients driven by multiplicative noise. The main…

Probability · Mathematics 2024-03-11 Wei Hong , Wei Liu , Luhan Yang

As a model for vortex-wall interactions, we consider the two-dimensional incompressible Navier--Stokes equations in the half-plane $R^2_+$ with no-slip boundary condition and point vortices as initial data. We focus on the paradigmatic…

Analysis of PDEs · Mathematics 2026-03-24 Anne-Laure Dalibard , Thierry Gallay

We show that any solution of the two-dimensional Navier-Stokes equation whose vorticity distribution is uniformly bounded in $L^1(R^2)$ for positive times is entirely determined by the trace of the vorticity at $t = 0$, which is a finite…

Analysis of PDEs · Mathematics 2007-05-23 Isabelle Gallagher , Thierry Gallay

We deal with a class of abstract nonlinear stochastic models, which covers many 2D hydrodynamical models including 2D Navier-Stokes equations, 2D MHD models and 2D magnetic B\'enard problem and also some shell models of turbulence. We first…

Probability · Mathematics 2011-12-15 Igor Chueshov , Annie Millet