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The aim of this paper is to develop tractable large deviation approximations for the empirical measure of a small noise diffusion. The starting point is the Freidlin-Wentzell theory, which shows how to approximate via a large deviation…

Probability · Mathematics 2021-01-11 Paul Dupuis , Guo-Jhen Wu

For continuous-time linear stochastic dynamical systems driven by Wiener processes, we consider the problem of designing ensemble filters when the observation process is randomly time-sampled. We propose a continuous-discrete McKean--Vlasov…

Optimization and Control · Mathematics 2024-06-21 Aneel Tanwani , Olga Yufereva

We study a discrete time multitype branching random walk on a finite space with finite set of types. Particles follow a Markov chain on the spatial space whereas offspring distributions are given by a random field that is fixed throughout…

Probability · Mathematics 2013-10-30 Onur Gün , Wolfgang König , Ozren Sekulović

The mean-field limit of a Markovian model describing the interaction of several classes of permanent connections in a network is analyzed. Each of the connections has a self-adaptive behavior in that its transmission rate along its route…

Probability · Mathematics 2009-12-15 Carl Graham , Philippe Robert

Classical results for exchangeable systems of random variables are extended to multi-class systems satisfying a natural partial exchangeability assumption. It is proved that the conditional law of a finite multi-class system, given the…

Probability · Mathematics 2008-10-16 Carl Graham

We study the mean-field limit of a generic class of dynamic co-evolving latent space networks motivated by the social and opinion dynamics literature. Such models include $n$ agents, whose opinions are given by latent stochastic processes,…

Probability · Mathematics 2026-04-24 Ankan Ganguly , Konstantinos Spiliopoulos , Daniel Sussman

We consider extended slow-fast systems of N interacting diffusions. The typical behavior of the empirical density is described by a nonlinear McKean-Vlasov equation depending on , the scaling parameter separating the time scale of the slow…

Analysis of PDEs · Mathematics 2021-08-09 Julien Barré , Cedric Bernardin , Raphaël Chétrite , Yash Chopra , Mauro Mariani

We study the applicability of the time-dependent variational principle in matrix product state manifolds for the long time description of quantum interacting systems. By studying integrable and nonintegrable systems for which the long time…

Strongly Correlated Electrons · Physics 2018-01-31 Benedikt Kloss , Yevgeny Bar Lev , David Reichman

We develop a unified theory to analyze the microcanonical ensembles with several constraints given by unbounded observables. Several interesting phenomena that do not occur in the single constraint case can happen under the multiple…

Probability · Mathematics 2019-01-24 Kyeongsik Nam

We present a Mean Field Game approach to obtain the rate function for the empirical measure of interacting particles under McKean-Vlasov dynamics. Although the result is well known, our approach relies on PDE methods and provides another…

Analysis of PDEs · Mathematics 2023-10-13 Nikiforos Mimikos-Stamatopoulos

In this paper, we prove a large deviation principle for the empirical measures of a system of weakly interacting diffusion with reflection. We adopt the weak convergence approach. To make this approach work, we show that the sequence of…

Probability · Mathematics 2023-04-04 Ping Cheng , Rong Wei , Tusheng Zhang

Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact representation, inference in such models is intractable even…

Artificial Intelligence · Computer Science 2012-05-14 Ido Cohn , Tal El-Hay , Nir Friedman , Raz Kupferman

We consider a general class of disordered mean-field models where both the spin variables and disorder variables take finitely many values. To investigate the size-dependence in the phase-transition regime we construct the metastate…

Mathematical Physics · Physics 2015-05-18 Giulio Iacobelli , Christof Kuelske

Stochastic interacting particle systems are widely used to model collective phenomena across diverse fields, including statistical physics, biology, and social dynamics. The McKean-Vlasov equation arises as the mean-field limit of such…

Computational Physics · Physics 2025-09-17 Zhiqiang Cai , Chengyu Liu , Xiang Zhou

We consider continuous-time Markov chains which display a family of wells at the same depth. We provide sufficient conditions which entail the convergence of the finite-dimensional distributions of the order parameter to the ones of a…

Probability · Mathematics 2019-10-03 Claudio Landim , Michail Loulakis , Mustapha Mourragui

The stochastic models investigated in this paper describe the evolution of a set of $F_N$ identical balls scattered into $N$ urns connected by an underlying symmetrical graph with constant degree $h_N$. After some random amount of time {\em…

Probability · Mathematics 2018-12-06 Wen Sun , Philippe Robert

We develop a mean-field theory for large, non-exchangeable particle (agent) systems where the states and interaction weights co-evolve in a coupled system of SDEs. A first main result is the establishment of the propagation of…

Probability · Mathematics 2025-12-30 Datong Zhou

The paper has two objectives: proving that the rate of convergence in distribution for mean-field models in CLT regime is $N^{-1/2}$, and obtaining explicit expressions for the infinitesimal generators of two types of measure-valued Markov…

Probability · Mathematics 2025-02-05 Xavier Erny

For finite size Markov chains, the Donsker-Varadhan theory fully describes the large deviations of the time averaged empirical measure. We are interested in the extension of the Donsker-Varadhan theory for a large size non-equilibrium…

Probability · Mathematics 2024-05-06 Thierry Bodineau , Benoit Dagallier

We consider a system consisting of $n$ particles, moving forward in jumps on the real line. System state is the empirical distribution of particle locations. Each particle ``jumps forward'' at some time points, with the instantaneous rate…

Probability · Mathematics 2023-03-03 Alexander Stolyar