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McKean-Vlasov limit for interacting random processes in random media

TLDR
In this paper, the authors apply large deviation theory to particle systems with a random mean-field interaction in the McKean-Vlasov limit and describe large deviations and normal fluctuations around the MCV equation.
Abstract
We apply large-deviation theory to particle systems with a random mean-field interaction in the McKean-Vlasov limit. In particular, we describe large deviations and normal fluctuations around the McKean-Vlasov equation. Due to the randomness in the interaction, the McKean-Vlasov equation is a collection of coupled PDEs indexed by the state space of the single components in the medium. As a result, the study of its solution and of the finite-size fluctuation around this solution requires some new ingredient as compared to existing techniques for nonrandom interaction.

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Journal ArticleDOI

The Kuramoto model: A simple paradigm for synchronization phenomena

TL;DR: In this paper, a review of the Kuramoto model of coupled phase oscillators is presented, with a rigorous mathematical treatment, specific numerical methods, and many variations and extensions of the original model that have appeared in the last few years.
Journal ArticleDOI

Mean-Field Backward Stochastic Differential Equations and Related Partial Differential Equations ∗

TL;DR: In this paper, a mean-field backward stochastic differential equation (SDE) is studied in a Markovian framework, associated with a McKean-Vlasov forward equation.
Journal ArticleDOI

Mean-field backward stochastic differential equations : a limit approach

TL;DR: In this paper, a special mean-field problem in a purely stochastic approach is investigated for the solution (Y, Z) of a mean field backward stochastastic differential equation with solution X, where coefficients are governed by N independent copies of (X-N, Y, N, Z, Z(N)).
Journal ArticleDOI

Metastability in stochastic dynamics of disordered mean-field models

TL;DR: In this article, the authors studied a class of Markov chains that describe reversible stochastic dynamics of a large class of disordered mean field models at low temperatures and gave a precise relation between the metastable time scales in the problem to the properties of the rate functions of the corresponding Gibbs measures.
Posted Content

Mean-field stochastic differential equations and associated PDEs

TL;DR: In this article, the authors considered a mean-field stochastic differential equation, also called Mc Kean-Vlasov equation, with initial data, where coefficients depend on both the solution and its law.
References
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Book

Brownian Motion and Stochastic Calculus

TL;DR: In this paper, the authors present a characterization of continuous local martingales with respect to Brownian motion in terms of Markov properties, including the strong Markov property, and a generalized version of the Ito rule.
Book

Markov Processes: Characterization and Convergence

TL;DR: In this paper, the authors present a flowchart of generator and Markov Processes, and show that the flowchart can be viewed as a branching process of a generator.
Book

Statistics of random processes

TL;DR: In this paper, the optimal linear non-stationary filtering, interpolation and extrapolation of Partially Observable Random Processes with a Countable Number of States (POMOS) was studied.
Book

Large deviations

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