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We consider a continuous time Markov chain on a countable state space and prove a joint large deviation principle for the empirical measure and the empirical flow, which accounts for the total number of jumps between pairs of states. We…

Probability · Mathematics 2015-01-19 Lorenzo Bertini , Alessandra Faggionato , Davide Gabrielli

We study particle systems with singular pairwise interactions and non-vanishing diffusion in the mean-field scaling. A classical approach to describing corrections to mean-field behavior is through the analysis of correlation functions. For…

Analysis of PDEs · Mathematics 2025-10-03 Mitia Duerinckx , Pierre-Emmanuel Jabin

We consider the context of molecular motors modelled by a diffusion process driven by the gradient of a weakly periodic potential that depends on an internal degree of freedom. The switch of the internal state, that can freely be…

Probability · Mathematics 2024-02-02 Serena Della Corte , Richard C. Kraaij

We study recursive maximum likelihood estimation for stochastic interacting particle systems based on continuous observation of a single particle. In this regime, consistent estimation of the finite-particle log-likelihood is not possible,…

Methodology · Statistics 2026-05-04 Louis Sharrock , Nikolas Kantas , Grigorios A. Pavliotis

This paper deals with rare events in a general {interacting gas} at high temperature, by means of Large Deviations Principles. The main result is an LDP for the tagged empirical field, which features the competition of an energy term and an…

Probability · Mathematics 2025-06-17 David Padilla-Garza

We consider stochastic differential systems driven by a Brownian motion and a Poisson point measure where the intensity measure of jumps depends on the solution. This behavior is natural for several physical models (such as Boltzmann…

Probability · Mathematics 2018-09-25 Vlad Bally , Dan Goreac , Victor Rabiet

A well-known It\^o formula for finite dimensional processes, given in terms of stochastic integrals with respect to Wiener processes and Poisson random measures, is revisited and is revised. The revised formula, which corresponds to the…

Probability · Mathematics 2020-07-30 István Gyöngy , Sizhou Wu

The so-called 'Level 2.5' general result for the large deviations of the joint probability of the density and of the currents for Markov Jump processes is applied to the case of $N$ independent particles on a ring with random transition…

Disordered Systems and Neural Networks · Physics 2021-05-12 Cecile Monthus

We consider the stochastic system of interacting neurons introduced in De Masi et al. (2015) and in Fournier and L\"ocherbach (2016) and then further studied in Erny, L\"ocherbach and Loukianova (2021) in a diffusive scaling. The system…

Probability · Mathematics 2022-11-30 Xavier Erny , Eva Löcherbach , Dasha Loukianova

We investigate the two-points correlation function for several boundary-driven interacting particle systems. Our goal is to show that the time evolution of that correlation function is solution to a partial differential equation that can be…

Probability · Mathematics 2024-10-24 P. Gonçalves , B. Salvador

We apply the large-deviation method to study trajectories in dissipative quantum systems. We show that in the long time limit the statistics of quantum jumps can be understood from thermodynamic arguments by exploiting the analogy between…

Statistical Mechanics · Physics 2010-04-20 Juan P. Garrahan , Igor Lesanovsky

Stochastic computational models in the form of pure jump processes occur frequently in the description of chemical reactive processes, of ion channel dynamics, and of the spread of infections in populations. For spatially extended models,…

Numerical Analysis · Mathematics 2018-02-23 Augustin Chevallier , Stefan Engblom

We consider a class of general SDEs with a jump integral term driven by a time-inhomogeneous Poisson random measure. We propose a two-parameters Euler-type scheme for this SDE class and prove an optimal rate for the strong convergence with…

Probability · Mathematics 2025-08-07 Mireille Bossy , Paul Maurer

We study the large deviation behavior of a system of diffusing particles with a mean field interaction, described through a collection of stochastic differential equations, in which each particle is driven by a vanishing independent…

Probability · Mathematics 2021-08-10 Amarjit Budhiraja , Michael Conroy

We develop the idea of non-Markovian CTRW (continuous time random walk) approximation to the evolution of interacting particle systems, which leads to a general class of fractional kinetic measure-valued evolutions with variable order. We…

Probability · Mathematics 2022-06-07 Vassili N. Kolokoltsov , Marianna S. Troeva

This paper provides a large deviation principle for Non-Markovian, Brownian motion driven stochastic differential equations with random coefficients. Similar to Gao and Liu \cite{GL}, this extends the corresponding results collected in…

Probability · Mathematics 2014-07-22 Jin Ma , Zhenjie Ren , Nizar Touzi , Jianfeng Zhang

We consider interacting systems particle driven by i.i.d. fractional Brownian motions, subject to irregular, possibly distributional, pairwise interactions. We show propagation of chaos and mean field convergence to the law of the…

Probability · Mathematics 2025-12-02 Lucio Galeati , Khoa Lê , Avi Mayorcas

We study fluctuations of mean-field interacting particle systems around their McKean--Vlasov limit. Our main result provides a uniform-in-time quantitative central limit theorem for the fluctuation process, with convergence rate of order…

Probability · Mathematics 2026-05-06 Solesne Bourguin , Konstantinos Spiliopoulos

A quantum system S undergoing continuous time measurement is usually described by a jump-diffusion stochastic differential equation. Such an equation is called a stochastic master equation and its solution is called a quantum trajectory.…

Mathematical Physics · Physics 2015-03-26 Tristan Benoist , Clement Pellegrini

This is a brief survey of laws of large numbers, fluctuation results and large deviation principles for asymmetric interacting particle systems that represent moving interfaces on the plane. We discuss the exclusion process, the Hammersley…

Probability · Mathematics 2009-11-24 Timo Seppalainen