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In this paper we investigate the asymptotic validity of boundary layer theory. For a flow induced by a periodic row of point-vortices, we compare Prandtl's solution to Navier-Stokes solutions at different $Re$ numbers. We show how Prandtl's…

Mathematical Physics · Physics 2015-01-21 Francesco Gargano , Marco Sammartino , Vincenzo Sciacca , Kevin Cassel

In this paper, we investigate the asymptotic behavior of solutions to the Navier-Stokes equations in the half-plane under high Reynolds number conditions, where the initial vorticity belongs to the Yudovich class and is supported away from…

Analysis of PDEs · Mathematics 2025-10-22 Jingchi Huang , Chao Wang , Jingchao Yue , Zhifei Zhang

Sampled-data (SD) systems, which are composed of both discrete- and continuous-time components, are arguably one of the most common classes of cyberphysical systems in practice; most modern controllers are implemented on digital platforms…

Systems and Control · Computer Science 2014-05-13 Shahab Kaynama , Jeremy H. Gillula , Claire J. Tomlin

We prove the existence and uniqueness of maximal solutions to the 3D SALT (Stochastic Advection by Lie Transport, [Holm arXiv:1410.8311]) Navier-Stokes Equation in velocity and vorticity form, on the torus and the bounded domain…

Analysis of PDEs · Mathematics 2022-11-03 Daniel Goodair , Dan Crisan

The Biot-Savart law is relevant in physical contexts including electromagnetism and fluid dynamics. In the latter case, when the rotation of a fluid is confined to a set of very thin vortex filaments, this law describes the velocity field…

Computational Physics · Physics 2025-07-10 Juan Ignacio Polanco

We show the absence of continuous symmetry breaking in 2D lattice systems without any smoothness assumptions on the interaction. We treat certain cases of interactions with integrable singularities. We also present cases of singular…

Probability · Mathematics 2011-08-25 Dima Ioffe , Senya Shlosman , Yvan Velenik

We consider a stochastic version of the point vortex system, in which the fluid velocity advects single vortices intermittently for small random times. Such system converges to the deterministic point vortex dynamics as the rate at which…

Probability · Mathematics 2023-11-28 Andrea Agazzi , Francesco Grotto , Jonathan C. Mattingly

We consider an interacting particle system modeled as a system of $N$ stochastic differential equations driven by Brownian motions. We prove that the (mollified) empirical process converges, uniformly in time and space variables, to the…

Probability · Mathematics 2020-10-19 Franco Flandoli , Christian Olivera , Marielle Simon

The long time behavior of a couple of interacting asymmetric exclusion processes of opposite velocities is investigated in one space dimension. We do not allow two particles at the same site, and a collision effect (exchange) takes place…

Probability · Mathematics 2009-11-10 Jozsef Fritz , Balint Toth

In this paper, we consider optimal control problems of stochastic Volterra equations (SVEs) with singular kernels, where the control domain is not necessarily convex. We establish a global maximum principle by means of the spike variation…

Probability · Mathematics 2025-03-11 Yushi Hamaguchi

We introduce a reaction-path statistical mechanics formalism based on the principle of large deviations to quantify the kinetics of single-molecule enzymatic reaction processes under the Michaelis-Menten mechanism, which exemplifies an…

Statistical Mechanics · Physics 2022-04-11 Hyuntae Lim , YounJoon Jung

We consider the incompressible 2D Navier-Stokes equations on the torus, driven by a deterministic time periodic force and a noise that is white in time and degenerate in Fourier space. The main result is twofold. Firstly, we establish a…

Probability · Mathematics 2023-07-13 Rongchang Liu , Kening Lu

In this article, we develop a framework to study the large deviation principle for matrix models and their quantized versions, by tilting the measures using the limits of spherical integrals obtained in [46,47]. As examples, we obtain 1. a…

Probability · Mathematics 2023-04-25 Serban Belinschi , Alice Guionnet , Jiaoyang Huang

We study the 2D Navier-Stokes equations within the framework of a constraint that ensures energy conservation throughout the solution. By employing the Galerkin approximation method, we demonstrate the existence and uniqueness of a global…

Analysis of PDEs · Mathematics 2023-07-13 Sangram Satpathi

In this article we establish a large deviation principle for the empirical measures of a simple spatially inhomogeneous random walk on $\overline{\mathbb{Z}}$, the two-point compactification of $\mathbb{Z}$. The classical Donsker--Varadhan…

Probability · Mathematics 2026-05-27 Jan-Luka Fatras

This is the second of two papers devoted to the asymptotic behavior of solutions to the incompressible Navier-Stokes equations in a half-space with point vortex initial data. A major difficulty stems from the interaction between the point…

Analysis of PDEs · Mathematics 2026-04-08 Chao Wang , Jingchao Yue , Zhifei Zhang

In this work we determine a process-level Large Deviation Principle (LDP) for a model of interacting particles indexed by a lattice $\mathbb{Z}^d$. The connections are random, sparse and unscaled, so that the system converges in the large…

Probability · Mathematics 2024-10-01 James MacLaurin

This paper considers a large class of nonlinear integro-differential scalar equations which involve an anomalous diffusion (e.g. driven by a fractional Laplacian) and a non-local singular convolution kernel. Each of those singular equations…

Probability · Mathematics 2025-01-07 Christian Olivera , Marielle Simon

This is the first of two papers concerning the asymptotic behavior of the incompressible Navier-Stokes equations in a half-space at high Reynolds numbers, with initial data given by a point vortex. In the present work, we establish the…

Analysis of PDEs · Mathematics 2026-04-08 Chao Wang , Jingchao Yue , Zhifei Zhang

We derive quantitative estimates proving the conditional propagation of chaos for large stochastic systems of interacting particles subject to both idiosyncratic and common noise. We obtain explicit bounds on the relative entropy between…

Probability · Mathematics 2024-07-02 Paul Nikolaev