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We study large deviations for random walks on stratified (Carnot) Lie groups. For such groups, there is a natural collection of vectors which generates their Lie algebra, and we consider random walks with increments in only these…

Probability · Mathematics 2024-08-16 Maria Gordina , Tai Melcher , Dan Mikulincer , Jing Wang

We consider the branching random walk drifting to $-\infty$ and we investigate large deviations-type estimates for the first passage time. We prove the corresponding law of large numbers and the central limit theorem.

Probability · Mathematics 2017-09-14 Dariusz Buraczewski , Mariusz Maslanka

We establish the (level-1) large deviation principles for three kinds of means associated with the backward continued fraction expansion. We show that: for the harmonic and geometric means, the rate functions vanish exactly at one point;…

Dynamical Systems · Mathematics 2019-12-30 Hiroki Takahasi

A method is introduced for studying large deviations in the context of statistical physics of disordered systems. The approach, based on an extension of the cavity method to atypical realizations of the quenched disorder, allows us to…

Disordered Systems and Neural Networks · Physics 2009-11-11 Olivier Rivoire

``Orderly divergence'' deals with limit theorems for weighted stochastic Gamma integrals of otherwise nonintegrable functions. Although for monotonic functions this category usually coincides with the classical notion of weighted limit…

Probability · Mathematics 2024-06-03 Jerzy Szulga

We consider partially directed walks crossing a $L\times L$ square weighted according to their length by a fugacity $t$. The exact solution of this model is computed in three different ways, depending on whether $t$ is less than, equal to…

Statistical Mechanics · Physics 2023-04-05 Nicholas R. Beaton , Aleksander L. Owczarek

We establish a comprehensive sample path large deviation principle (LDP) for log-processes associated with multivariate time-inhomogeneous stochastic volatility models. Examples of models for which the new LDP holds include Gaussian models,…

Probability · Mathematics 2022-11-15 Archil Gulisashvili

The paper concerns itself with establishing large deviation principles for a sequence of stochastic integrals and stochastic differential equations driven by general semimartingales in infinite-dimensional settings. The class of…

Probability · Mathematics 2017-08-25 Arnab Ganguly

We study large deviations of a ratio observable in discrete-time reset processes. The ratio takes the form of a current divided by the number of reset steps and as such it is not extensive in time. A large deviation rate function can be…

Statistical Mechanics · Physics 2020-04-21 Francesco Coghi , Rosemary J. Harris

We derive properties of the rate function in Varadhan's (annealed) large deviation principle for multidimensional, ballistic random walk in random environment, in a certain neighborhood of the zero set of the rate function. Our approach…

Probability · Mathematics 2016-06-14 Jonathon Peterson , Ofer Zeitouni

We suggest a new Hamiltonian lattice approach, using a regularisation motivated by deep inelastic scattering. We discuss the relation between distribution functions and the $F_1$ structure function. We have tested this method by computing…

High Energy Physics - Lattice · Physics 2009-10-28 Helmut Kroger , Norbert Scheu

The Galton--Watson process is the simplest example of a branching process. The relationship between the offspring distribution, and, when the extinction occurs almost surely, the distribution of the total progeny is well known. In this…

Probability · Mathematics 2017-04-10 Claudio Macci , Barbara Pacchiarotti

We investigate a model of continuous-time simple random walk paths in $\mathbb{Z}^d$ undergoing two competing interactions: an attractive one towards the large values of a random potential, and a self-repellent one in the spirit of the…

We propose a randomized lattice algorithm for approximating multivariate periodic functions over the $d$-dimensional unit cube from the weighted Korobov space with mixed smoothness $\alpha > 1/2$ and product weights…

Numerical Analysis · Mathematics 2025-08-26 Mou Cai , Takashi Goda , Yoshihito Kazashi

We prove large deviation principles for two versions of fractional Poisson processes. Firstly we consider the main version which is a renewal process; we also present large deviation estimates for the ruin probabilities of an insurance…

Probability · Mathematics 2016-11-26 Luisa Beghin , Claudio Macci

In a general class of one dimensional random differential equation the convergence of the distribution function of the solution to stationary state distribution is studied. In particular it is proved the boundedness respectively the…

Probability · Mathematics 2010-07-07 Gyorgy Steinbrecher , Xavier Garbet , Boris Weyssow

We show that a very simple randomised algorithm for numerical integration can produce a near optimal rate of convergence for integrals of functions in the $d$-dimensional weighted Korobov space. This algorithm uses a lattice rule with a…

Numerical Analysis · Mathematics 2023-04-21 Frances Y. Kuo , Dirk Nuyens , Laurence Wilkes

This paper investigates the large deviation problem in the sample path space of the nearest-neighbor random walks on regular trees. We establish the sample path large deviation principle for the law of the distance from a nearest random…

Probability · Mathematics 2025-05-07 Jie Jiang , Shuwen Lai

Motivated by the recent advances in the theory of stochastic partial differential equations involving nonlinear functions of distributions, like the Kardar-Parisi-Zhang (KPZ) equation, we reconsider the unique solvability of one-dimensional…

Probability · Mathematics 2015-03-09 François Delarue , Roland Diel

We consider a directed variant of the negative-weight percolation model in a two-dimensional, periodic, square lattice. The problem exhibits edge weights which are taken from a distribution that allows for both positive and negative values.…

Disordered Systems and Neural Networks · Physics 2019-08-21 Christoph Norrenbrock , Mitchell M. Mkrtchian , Alexander K. Hartmann