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A large deviation principle is established for a general class of stochastic flows in the small noise limit. This result is then applied to a Bayesian formulation of an image matching problem, and an approximate maximum likelihood property…

Statistics Theory · Mathematics 2010-02-24 Amarjit Budhiraja , Paul Dupuis , Vasileios Maroulas

We present a review of recent work on the statistical mechanics of non equilibrium processes based on the analysis of large deviations properties of microscopic systems. Stochastic lattice gases are non trivial models of such phenomena and…

Probability · Mathematics 2015-12-18 L. Bertini , A. De Sole , D. Gabrielli , G. Jona-Lasinio , C. Landim

We consider a two-dimensional Hamiltonian system perturbed by a small diffusion term, whose coefficient is state-dependent and non-degenerate. As a result, the process consists of the fast motion along the level curves and slow motion…

Probability · Mathematics 2022-05-24 Shuo Yan

We study the large deviations of sums of correlated random variables described by a matrix product ansatz, which generalizes the product structure of independent random variables to matrices whose non-commutativity is the source of…

Statistical Mechanics · Physics 2014-02-18 Florian Angeletti , Hugo Touchette , Eric Bertin , Patrice Abry

In this paper, we study the cut-off phenomenon under the total variation distance of $d$-dimensional Ornstein-Uhlenbeck processes which are driven by L\'evy processes. That is to say, under the total variation distance, there is an abrupt…

Probability · Mathematics 2023-05-05 Gerardo Barrera , Juan Carlos Pardo

In this article, we introduce Mittag-Leffler L\'evy process and provide two alternative representations of this process. First, in terms of Laplace transform of the marginal densities and next as a subordinated stochastic process. Both…

Probability · Mathematics 2016-02-05 Arun Kumar , N. S. Upadhye

A new approach for the analysis of Langevin-type stochastic processes in the presence of strong measurement noise is presented. For the case of Gaussian distributed, exponentially correlated, measurement noise it is possible to extract the…

Data Analysis, Statistics and Probability · Physics 2013-05-29 Bernd Lehle

In this paper, we study an approximation scheme for L\'evy processes with drift in terms of a representation that is akin to the celebrated Mehler formula for L\'evy-Ornstein-Uhlenbeck processes. The approximation scheme is based on a…

Probability · Mathematics 2025-11-25 Max Nendel

Suppose Xt is either a regular exponential type Levy process or a Levy process with a bounded variation jumps measure. The distribution of the extrema of Xt play a crucial role in many financial and actuarial problems. This article employs…

Probability · Mathematics 2017-01-23 Amir T. Payandeh Najafabadi , Dan Kucerovsky

The incidence of rare events in fast-slow systems is investigated via analysis of the large deviation principle (LDP) that characterizes the likelihood and pathway of large fluctuations of the slow variables away from their mean behavior --…

Statistical Mechanics · Physics 2016-02-17 Freddy Bouchet , Tobias Grafke , Tomás Tangarife , Eric Vanden-Eijnden

We derive some large deviation bounds for events related to the "true self-repelling motion", a one-dimensional self-interacting process introduced by Toth and Werner, that has very different path properties than usual diffusion processes.…

Probability · Mathematics 2012-07-16 Laure Dumaz

This paper considers discretization of the L\'evy process appearing in the Lamperti representation of a strictly positive self-similar Markov process. Limit theorems for the resulting approximation are established under some regularity…

Probability · Mathematics 2020-06-17 Jevgenijs Ivanovs , Jakob D. Thøstesen

We consider a modulated process S which, conditional on a background process X, has independent increments. Assuming that S drifts to -infinity and that its increments (jumps) are heavy-tailed (in a sense made precise in the paper), we…

Probability · Mathematics 2017-11-29 Sergey Foss , Takis Konstantopoulos , Stan Zachary

Let $\{{\bf \mathcal{Z}}_n:n\geq 1\}$ be a sequence of i.i.d. random probability measures. Independently, for each $n\geq 1$, let $(X_{n1},\ldots, X_{nn})$ be a random vector of positive random variables that add up to one. This paper…

Probability · Mathematics 2021-06-24 Shui Feng

We prove a large deviation principle for the point process associated to $k$-element connected components in $\mathbb R^d$ with respect to the connectivity radii $r_n\to\infty$. The random points are generated from a homogeneous Poisson…

Probability · Mathematics 2022-10-19 Christian Hirsch , Takashi Owada

In this paper we establish limit theorems for power variations of stochastic processes controlled by fractional Brownian motions with Hurst parameter $H\leq 1/2$. We show that the power variations of such processes can be decomposed into…

Probability · Mathematics 2023-09-08 Yanghui Liu , Xiaohua Wang

This paper concerns the large deviations of a system of interacting particles on a random graph. There is no stochasticity, and the only sources of disorder are the random graph connections, and the initial condition. The average number of…

Probability · Mathematics 2021-03-08 James MacLaurin

We derive theorems which outline explicit mechanisms by which anomalous scaling for the probability density function of the sum of many correlated random variables asymptotically prevails. The results characterize general anomalous scaling…

Statistical Mechanics · Physics 2015-05-14 Attilio L. Stella , Fulvio Baldovin

The event of large losses plays an important role in credit risk. As these large losses are typically rare, and portfolios usually consist of a large number of positions, large deviation theory is the natural tool to analyze the tail…

Probability · Mathematics 2014-07-03 Vincent Leijdekker , Michel Mandjes , Peter Spreij

Skewness and kurtosis are fundamental statistical moments commonly used to quantify asymmetry and tail behavior in probability distributions. Despite their widespread application in statistical mechanics, condensed matter physics, and…

Mathematical Physics · Physics 2025-06-23 Carlo De Michele , Samuele De Bartolo