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In this paper we analyze a coupling between the very large jumps in physical and operational times as applied to anomalous diffusion. The approach is based on subordination of a skewed Levy-stable process by its inverse to get two types of…

Statistical Mechanics · Physics 2011-11-15 Aleksander Stanislavsky , Karina Weron

This work studies a two-time-scale functional system given by two jump-diffusions under the scale separation by a small parameter $\varepsilon \rightarrow 0$. The coefficients of the equations that govern the dynamics of the system depend…

Probability · Mathematics 2022-07-15 André de Oliveira Gomes , Pedro Catuogno

In this paper, we introduce a mathematical apparatus that is relevant for understanding a dynamical system with small random perturbations and coupled with the so-called transmutation process -- where the latter jumps from one mode to…

Dynamical Systems · Mathematics 2017-09-15 Getachew K. Befekadu

Motivated by the study of rare events for a typical genetic switching model in systems biology, in this paper we aim to establish the general two-scale large deviations for chemical reaction systems. We build a formal approach to explicitly…

Statistical Mechanics · Physics 2016-04-13 Tiejun Li , Feng Lin

We present a large deviation principle for some stochastic evolution equations with jumps which depend on two small parameters, when the viscosity parameter {\epsilon} tends to zero more quickly than the homogenization's one…

Dynamical Systems · Mathematics 2019-10-29 C. Manga , A. Aman , A. Coulibaly , A. Diédhiou

For Markov processes evolving on multiple time-scales a combination of large component scalings and averaging of rapid fluctuations can lead to useful limits for model approximation. A general approach to proving a law of large numbers to a…

Probability · Mathematics 2020-12-29 Lea Popovic

We provide Large Deviation estimates for the bridge of a $d$-dimensional general diffusion process as the conditioning time tends to $0$ and apply these results to the evaluation of the asymptotics of its exit time probabilities. We are…

Probability · Mathematics 2014-06-19 Paolo Baldi , Lucia Caramellino , Maurizia Rossi

Convergence of stochastic processes with jumps to diffusion processes is investigated in the case when the limit process has discontinuous coefficients. An example is given in which the diffusion approximation of a queueing model yields a…

Probability · Mathematics 2016-09-07 N. V. Krylov , R. Liptser

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 present large deviations estimates in the supremum norm for a system of independent random walks superposed with a birth-and-death dynamics evolving on the discrete torus with $N$ sites. The scaling limit considered is the so-called…

Probability · Mathematics 2021-02-26 Tertuliano Franco , Luana A. Gurgel , Bernardo N. B. de Lima

We consider a diffusion process on $\mathbb R^n$ and prove a large deviation principle for the empirical process in the joint limit in which the time window diverges and the noise vanishes. The corresponding rate function is given by the…

Probability · Mathematics 2024-12-31 Lorenzo Bertini , Davide Gabrielli , Claudio Landim

We consider quantum stochastic processes and discuss a level 2.5 large deviation formalism providing an explicit and complete characterisation of fluctuations of time-averaged quantities, in the large-time limit. We analyse two classes of…

Statistical Mechanics · Physics 2021-08-03 Federico Carollo , Juan P. Garrahan , Robert L. Jack

Linear diffusions are used to model a large number of stochastic processes in physics, including small mechanical and electrical systems perturbed by thermal noise, as well as Brownian particles controlled by electrical and optical forces.…

Statistical Mechanics · Physics 2023-05-10 Johan du Buisson , Hugo Touchette

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

We propose a general framework for studying jump-diffusion systems driven by both Gaussian noise and a jump process with state-dependent intensity. Of particular natural interest are the jump locations: the system evaluated at the jump…

Statistical Mechanics · Physics 2018-09-28 Christopher E. Miles , James P. Keener

The Whittaker 2d growth model is a triangular continuous Markov diffusion process that appears in many scientific contexts. It has been theoretically intriguing to establish a large deviation principle for this 2d process with a scaling…

Probability · Mathematics 2020-09-29 Jun Gao , Jie Ding

In this paper we study the large deviations of time averaged mean square displacement (TAMSD) for Gaussian processes. The theory of large deviations is related to the exponential decay of probabilities of large fluctuations in random…

Probability · Mathematics 2018-11-29 J. Gajda , A. Wylomanska , H. Kantz , A. V. Chechkin , G. Sikora

We investigate the convergence of hitting times for jump-diffusion processes. Specifically, we study a sequence of stochastic differential equations with jumps. Under reasonable assumptions, we establish the convergence of solutions to the…

Probability · Mathematics 2015-10-09 Georgiy Shevchenko

We consider a diffusion equation in $\mathbb{R}^d$ with drift equal to the gradient of a homogeneous potential of degree $1+\gamma$, with $0<\gamma<1$, and local variance equal to $\varepsilon^2$ with $\varepsilon\to 0$. The associated…

Probability · Mathematics 2026-03-04 Paola Bermolen , Valeria Goicoechea , José R. León

We consider large deviations of empirical measures of diffusion processes. In a first part, we present conditions to obtain a large deviations principle (LDP) for a precise class of unbounded functions. This provides an analogue to the…

Probability · Mathematics 2020-09-23 Grégoire Ferré , Gabriel Stoltz