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A particle with internal unobserved states diffusing in a force field will generally display effective advection-diffusion. The drift velocity is proportional to the mobility averaged over the internal states, or effective mobility, while…

Statistical Mechanics · Physics 2017-10-13 Erik Aurell , Stefano Bo

We study the distribution of the magnetization of the critical mean-field O(N) model with N > 1. Specifically, we bound the Wasserstein distance between the finite-volume and limiting distributions, in terms of the number of spins. To…

Probability · Mathematics 2025-12-08 Timothy M. Garoni , Aram Perez , Zongzheng Zhou

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

In the nonlinear diffusion framework, stochastic processes of McKean-Vlasov type play an important role. In some cases they correspond to processes attracted by their own probability distribution: the so-called self-stabilizing processes.…

Probability · Mathematics 2014-09-04 Samuel Herrmann , Julian Tugaut

Despite spatial and temporal fluctuations in turbulent astrophysical systems, mean-field theories can be used to describe their secular evolution. However, observations taken over time scales much shorter than dynamical time scales capture…

High Energy Astrophysical Phenomena · Physics 2021-09-08 Hongzhe Zhou , Eric G. Blackman

We study a nonlinear, degenerate cross-diffusion model which involves two densities with two different drift velocities. A general framework is introduced based on its gradient flow structure in Wasserstein space to derive a notion of…

Analysis of PDEs · Mathematics 2018-03-20 Inwon Kim , Alpár R. Mészáros

We consider a system of diffusion processes that interact through their empirical mean and have a stabilizing force acting on each of them, corresponding to a bistable potential. There are three parameters that characterize the system: the…

Risk Management · Quantitative Finance 2012-08-31 Josselin Garnier , George Papanicolaou , Tzu-Wei Yang

This work presents the first systematic development of Stein's method for matrix distributions. We establish the basic essential ingredients of Stein's method for matrix normal approximation: we derive a generator-based Stein identity from…

Statistics Theory · Mathematics 2026-01-19 Robert E. Gaunt , Frédéric Ouimet , Donald Richards

By using the spectrum of the underlying symmetric diffusion operator, the convergence in $L^p$-Wasserstein distance $\mathbb W_p (p\ge 1)$ is characterized for the empirical measure $\mu_t$ of non-symmetric subordinated diffusion processes…

Probability · Mathematics 2023-02-28 Feng-Yu Wang

In this work, we focus on the mean-field limit of the Random Batch Method (RBM) for the Cucker-Smale model. Different from the classical mean-field limit analysis, the chaos in this model is imposed at discrete time and is propagated to…

Numerical Analysis · Mathematics 2024-08-01 Yuelin Wang , Yiwen Lin

In this work, we investigate links between the formulation of the flow of marginals of reversible diffusion processes as gradient flows in the space of probability measures and path wise large deviation principles for sequences of such…

Probability · Mathematics 2014-05-16 Max Fathi

The diffraction patterns of crystalline materials with strongly-correlated disorder are characterised by the presence of structured diffuse scattering. Conventional analysis approaches generally seek to interpret this scattering either…

Disordered Systems and Neural Networks · Physics 2021-07-29 Ella M. Schmidt , Johnathan M. Bulled , Andrew L. Goodwin

We provide explicit bounds on the Wasserstein distance between discrete time martingales and the standard normal distribution. The proofs are based on a combination of Lindeberg's and Stein's method.

Probability · Mathematics 2018-08-14 Adrian Röllin

This paper establishes central limit theorems for Polyak-Ruppert averaged Q-learning under asynchronous updates. We prove a non-asymptotic central limit theorem, where the convergence rate in Wasserstein distance explicitly reflects the…

Machine Learning · Computer Science 2026-04-21 Xingtu Liu

In this note, we consider generalizations of the Cucker-Smale dynamical system and we derive rigorously in Wasserstein's type topologies the mean-field limit (and propagation of chaos) to the Vlasov-type equation introduced in [12].Unlike…

Analysis of PDEs · Mathematics 2021-02-10 Roberto Natalini , Thierry Paul

We present a novel approximate inference method for diffusion processes, based on the Wasserstein gradient flow formulation of the diffusion. In this formulation, the time-dependent density of the diffusion is derived as the limit of…

Machine Learning · Statistics 2018-06-13 Charlie Frogner , Tomaso Poggio

Mean-field theory is an approximation replacing an extended system by a few variables. For depinning of elastic manifolds, these are the position of its center of mass $u$, and the statistics of the forces $F(u)$. There are two proposals to…

Statistical Mechanics · Physics 2022-01-19 Cathelijne ter Burg , Kay Joerg Wiese

In the limit of a nonlinear diffusion model involving the fractional Laplacian we get a "mean field" equation arising in superconductivity and superfluidity. For this equation, we obtain uniqueness, universal bounds and regularity results.…

Analysis of PDEs · Mathematics 2012-06-29 Sylvia Serfaty , Juan Luis Vazquez

In this paper, we develop a stochastic algorithm based on Euler-Maruyama scheme to approximate the invariant measure of the limiting multidimensional diffusion of the $M/Ph/n+M$ queue. Specifically, we prove a non-asymptotic error bound…

Probability · Mathematics 2021-12-21 Xinghu Jin , Guodong Pang , Lihu Xu , Xin Xu

We consider a non-nestling random walk in a product random environment. We assume an exponential moment for the step of the walk, uniformly in the environment. We prove an invariance principle (functional central limit theorem) under almost…

Probability · Mathematics 2007-06-13 Firas Rassoul-Agha , Timo Seppalainen
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