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We prove a functional limit theorem for vector-valued functionals of the fractional Ornstein-Uhlenbeck process, providing the foundation for the fluctuation theory of slow/fast systems driven by such a noise. Our main contribution is on the…

Probability · Mathematics 2023-03-07 Johann Gehringer , Xue-Mei Li

We consider the inverse problem of determining different type of information about a diffusion process, described by ordinary or fractional diffusion equations stated on a bounded domain, like the density of the medium or the velocity field…

Analysis of PDEs · Mathematics 2019-07-05 Yavar Kian , Zhiyuan Li , Yikan Liu , Masahiro Yamamoto

We consider a diffusion process with coefficients that are periodic outside of an 'interface region' of finite thickness. The question investigated in the articles [1,2] is the limiting long time / large scale behaviour of such a process…

Probability · Mathematics 2009-10-05 Martin Hairer , Charles Manson

A basic result of large deviations theory is Sanov's theorem, which states that the sequence of empirical measures of independent and identically distributed samples satisfies the large deviation principle with rate function given by…

Probability · Mathematics 2014-10-17 Markus Fischer

The Pearson family of ergodic diffusions with a quadratic diffusion coefficient and a linear force are characterized by explicit dynamics of their integer moments and by explicit relaxation spectral properties towards their steady state.…

Statistical Mechanics · Physics 2023-08-14 Cecile Monthus

The aim of the present paper is to extend the large deviation with discontinuous statistics studied in \cite{BDE} to the diffusion $d\mathbf{x}^\varepsilon = -\{\mathbf{A}^\top (\mathbf{A} \mathbf{x}^\varepsilon - \mathbf{y}) + \mu…

Probability · Mathematics 2016-10-04 Azzouz Dermoune , Khalifa Es-Sebaiy , Youssef Ouknine

We study the large deviation rate functional for the empirical distribution of independent Brownian particles with drift. In one dimension, it has been shown by Adams, Dirr, Peletier and Zimmer that this functional is asymptotically…

Probability · Mathematics 2016-01-11 Matthias Erbar , Jan Maas , Michiel Renger

We derive an annealed large deviation principle (LDP) for the normalised and rescaled local times of a continuous-time random walk among random conductances (RWRC) in a time-dependent, growing box in $\Z^d$. We work in the interesting case…

Probability · Mathematics 2013-08-22 Wolfgang König , Tilman Wolff

For a heat equation with memory driven by a L\'evy-type noise we establish the existence of a unique solution. The main part of the article focuses on the Freidlin-Wentzell large deviation principle of the solutions of heat equation with…

Probability · Mathematics 2016-12-01 Markus Riedle , Jianliang Zhai

We consider the asymptotic behavior of the fluctuations for the empirical measures of interacting particle systems with singular kernels. We prove that the sequence of fluctuation processes converges in distribution to a generalized…

Probability · Mathematics 2024-12-31 Zhenfu Wang , Xianliang Zhao , Rongchan Zhu

We introduce stochastic volatility models, in which the volatility is described by a time-dependent nonnegative function of a reflecting diffusion. The idea to use reflecting diffusions as building blocks of the volatility came into being…

Mathematical Finance · Quantitative Finance 2020-06-30 Archil Gulisashvili

We establish a large deviation principle for time dependent trajectories (paths) of the empirical density of $N$ particles with long range interactions, for homogeneous systems. This result extends the classical kinetic theory that leads to…

Statistical Mechanics · Physics 2022-01-19 Ouassim Feliachi , Freddy Bouchet

We have considered a one-dimensional coagulation-decoagulation system of classical particles on a finite lattice with reflecting boundaries. It is known that the system undergoes a phase transition from a high-density to a low-density…

Statistical Mechanics · Physics 2013-10-03 Pegah Torkaman , Farhad H. Jafarpour

This work concerns generalized backward stochastic differential equations, which are coupled with a family of reflecting diffusion processes. First of all, we establish the large deviation principle for forward stochastic differential…

Probability · Mathematics 2024-07-23 Yawen Liu , Huijie Qiao

We obtain strong consistency and asymptotic normality of a least squares estimator of the drift coefficient for complex-valued Ornstein-Uhlenbeck processes disturbed by fractional noise, extending the result of Y. Hu and D. Nualart,…

Probability · Mathematics 2017-01-27 Yong Chen , Yaozhong Hu , Zhi Wang

Large deviation functions are an essential tool in the statistics of rare events. Often they can be obtained by contraction from a so-called level 2 large deviation {\em functional} characterizing the empirical density of the underlying…

Statistical Mechanics · Physics 2016-08-24 Johannes Hoppenau , Daniel Nickelsen , Andreas Engel

This paper is mainly concerned with the large deviation principle of the fractional McKean-Vlasov stochastic reaction-diffusion equation defined on R^n with polynomial drift of any degree. We first prove the well-posedness of the underlying…

Probability · Mathematics 2024-06-18 Zhang Chen , Bixiang Wang

In this work we present a general derivation of the non-Fickian behavior for the self-diffusion of identically interacting particle systems with excluded mutual passage. We show that the conditional probability distribution of finding a…

Statistical Mechanics · Physics 2009-11-07 Markus Kollmann

We prove a law of large numbers and a central limit theorem for a tagged particle in a symmetric simple exclusion process in the one-dimensional lattice with variable diffusion coefficient. The scaling limits are obtained from a similar…

Statistical Mechanics · Physics 2009-04-24 Milton Jara , Patricia Goncalves

The one-dimensional motion of any number $\cN$ of particles in the field of many independent waves (with strong spatial correlation) is formulated as a second-order system of stochastic differential equations, driven by two Wiener…

Probability · Mathematics 2014-04-10 Yves Elskens , Etienne Pardoux
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