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We generalize the theory of periodic homogenization for multidimensional SDEs with additive Brownian and stable L\'evy noise for $\alpha\in (1,2)$ to the setting of singular periodic Besov drifts of regularity $\beta\in ((2-2\alpha)/3,0)$…

Probability · Mathematics 2023-09-29 Helena Kremp , Nicolas Perkowski

We consider one-hidden layer neural networks trained in the feature-learning regime using gradient descent, and relate the output of the finite-width network $f_{\hat{\rho}_t^m}$ to its infinite-width counterpart $f_{\rho_t^{MF}}$, which…

Machine Learning · Statistics 2026-05-22 Margalit Glasgow , Joan Bruna

In this paper we give a quantitative stability result for the discrete interaction energy on the multi-dimensional torus, for the periodic Riesz potential. It states that if the number of particles $N$ is large and the discrete interaction…

Analysis of PDEs · Mathematics 2024-07-29 Ruiwen Shu

The well-posedness for SDEs with singularity in both space and distribution variables is derived, where the interacting drift term is bounded and Lipschitz continuous under total variation distance and the diffusion term is allowed to be…

Probability · Mathematics 2025-07-25 Xing Huang

We present a methodology to construct efficient high-order in time accurate numerical schemes for a class of gradient flows with appropriate Lipschitz continuous nonlinearity. There are several ingredients to the strategy: the exponential…

Numerical Analysis · Mathematics 2021-02-23 Wenbin Chen , Shufen Wang , Xiaoming Wang

We investigate the regularizing effect of certain perturbations by noise in singular interacting particle systems under the mean field scaling. In particular, we show that the addition of a suitably irregular path can regularise these…

Probability · Mathematics 2023-04-26 Fabian Harang , Avi Mayorcas

We study first- and second-order linear transport equations, as well as ODE and SDE flows, with velocity fields satisfying a one-sided Lipschitz condition. Depending on the time direction, the flows are either compressive or expansive. In…

Analysis of PDEs · Mathematics 2023-06-26 Pierre-Louis Lions , Benjamin Seeger

We study the quantitative convergence of drift-diffusion PDEs that arise as Wasserstein gradient flows of linearly convex functions over the space of probability measures on ${\mathbb R}^d$. In this setting, the objective is in general not…

Optimization and Control · Mathematics 2025-07-17 Lénaïc Chizat , Maria Colombo , Xavier Fernández-Real

We consider a system of N point particles moving on a d-dimensional torus. Each particle is subject to a uniform field E and random speed conserving collisions. This model is a variant of the Drude-Lorentz model of electrical conduction. In…

Mathematical Physics · Physics 2015-06-16 F. Bonetto , E. A. Carlen , R. Esposito , J. L. Lebowitz , R. Marra

We study the long time behavior of second order particle systems interacting through global Lipschitz kernels. Combining hypocoercivity method in [37] and relative entropy method in [25], we are able to overcome the degeneracy of diffusion…

Analysis of PDEs · Mathematics 2024-09-05 Yun Gong , Zhenfu Wang , Pengzhi Xie

In the framework of the concept of time correlation functions, we develop a self-consistent relaxation theory of the transverse collective particle dynamics in liquids. The theory agrees with well-known results in both the short-wave (free…

Soft Condensed Matter · Physics 2021-03-11 A. V. Mokshin , R. M. Khusnutdinoff , Ya. Z. Vilf , B. N. Galimzyanov

In this article we show, in a concise manner, a result of uniform in time propagation of chaos for non exchangeable systems of particles interacting according to a random graph. Provided the interaction is Lipschitz continuous, the…

Probability · Mathematics 2023-04-18 Pierre Le Bris , Christophe Poquet

We consider backward stochastic differential equations (BSDEs) with mean-field and McKean-Vlasov interactions in their generators in a general setting, where the drivers are square-integrable martingales, with a focus on the independent…

Probability · Mathematics 2024-08-27 Antonis Papapantoleon , Alexandros Saplaouras , Stefanos Theodorakopoulos

The classical (overdamped) Langevin dynamics provide a natural algorithm for sampling from its invariant measure, which uniquely minimizes an energy functional over the space of probability measures, and which concentrates around the…

Probability · Mathematics 2023-09-26 Giovanni Conforti , Daniel Lacker , Soumik Pal

Motivated by considerations from neuroscience (macroscopic behavior of large ensembles of interacting neurons), we consider a population of mean field interacting diffusions in $\mathbf {R}^m$ in the presence of a random environment and…

Probability · Mathematics 2014-07-03 Eric Luçon , Wilhelm Stannat

We consider a geodesic flow on a compact manifold endowed with a Riemannian (or Finsler, or Lorentz) metric satisfying some generic, explicit conditions. We couple the geodesic flow with a time-dependent potential, driven by an external…

Dynamical Systems · Mathematics 2013-07-08 Marian Gidea , Rafael de la Llave

We study the mean field Langevin dynamics and the associated particle system. By assuming the functional convexity of the energy, we obtain the $L^p$-convergence of the marginal distributions towards the unique invariant measure for the…

Probability · Mathematics 2025-11-06 Fan Chen , Zhenjie Ren , Songbo Wang

This article is a continuation of our first work \cite{chaudruraynal:frikha}. We here establish some new quantitative estimates for propagation of chaos of non-linear stochastic differential equations in the sense of McKean-Vlasov. We…

Analysis of PDEs · Mathematics 2021-08-26 Noufel Frikha , Paul-Eric Chaudru de Raynal

We develop a unified relative entropy framework for macroscopic limits of kinetic equations with Riesz-type interactions and Fokker-Planck relaxation. Our analysis covers three prototypical singular regimes: the diffusive limit leading to a…

Analysis of PDEs · Mathematics 2026-04-21 Young-Pil Choi , Jinwook Jung

We model the evolution of tokens within a deep stack of Transformer layers as a continuous-time flow on the unit sphere, governed by a mean-field interacting particle system, building on the framework introduced in (Geshkovski et al.,…

Machine Learning · Computer Science 2025-04-17 Giuseppe Bruno , Federico Pasqualotto , Andrea Agazzi