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We prove large deviations principles for spectral measures of perturbed (or spiked) matrix models in the direction of an eigenvector of the perturbation. In each model under study, we provide two approaches, one of which relying on large…

Probability · Mathematics 2021-09-24 Nathan Noiry , Alain Rouault

We obtain large deviation results for a two time-scale model of jump-diffusion processes. The processes on the two time scales are fully inter-dependent, the slow process has small perturbative noise and the fast process is ergodic. Our…

Probability · Mathematics 2016-09-19 Rohini Kumar , Lea Popovic

We show existence of the weak large deviation principle, with a convex rate function, for the renormalized distance from the starting point of irreducible random walks on relatively hyperbolic groups. Under the assumption of finiteness of…

Probability · Mathematics 2021-11-30 Emilio Corso

Fleming-Viot type particle systems represent a classical way to approximate the distribution of a Markov process with killing, given that it is still alive at a final deterministic time. In this context, each particle evolves independently…

Probability · Mathematics 2017-09-21 Bernard Delyon , Frédéric Cérou , Arnaud Guyader , Mathias Rousset

We study Mallows random permutations conditioned to avoid a given pattern $\alpha$ of length~$3$. When the bias parameter is of the form $e^{\beta/n}$, we prove that these permutations converge to a non-trivial explicit deterministic…

Probability · Mathematics 2026-04-28 Thomas Budzinski , Victor Dubach , Valentin Féray , Mohamed Slim Kammoun , Mylène Maïda

We study the performance of machine learning binary classification techniques in terms of error probabilities. The statistical test is based on the Data-Driven Decision Function (D3F), learned in the training phase, i.e., what is…

Machine Learning · Computer Science 2023-01-19 Paolo Braca , Leonardo M. Millefiori , Augusto Aubry , Antonio De Maio , Peter Willett

We investigate the probabilities of large deviations for the position of the front in a stochastic model of the reaction $X+Y \to 2X$ on the integer lattice in which $Y$ particles do not move while $X$ particles move as independent simple…

Probability · Mathematics 2008-07-16 Jean Bérard , Alejandro Ramírez

A standard approach to computing expectations with respect to a given target measure is to introduce an overdamped Langevin equation which is reversible with respect to the target distribution, and to approximate the expectation by a…

Numerical Analysis · Mathematics 2016-04-20 A. B. Duncan , T. Lelievre , G. A. Pavliotis

We consider a single genetic locus with two alleles $A_1$ and $A_2$ in a large haploid population. The locus is subject to selection and two-way, or recurrent, mutation. Assuming the allele frequencies follow a Wright-Fisher diffusion and…

Probability · Mathematics 2024-04-29 Wai-Tong Louis Fan , John Wakeley

The configuration model is a sequence of random graphs constructed such that in the large network limit the degree distribution converges to a pre-specified probability distribution. The component structure of such random graphs can be…

Probability · Mathematics 2019-12-12 Shankar Bhamidi , Amarjit Budhiraja , Paul Dupuis , Ruoyu Wu

We consider a class of tempered subordinators, namely a class of subordinators with one-dimensional marginal tempered distributions which belong to a family studied in [3]. The main contribution in this paper is a non-central moderate…

Probability · Mathematics 2020-11-05 Nikolai Leonenko , Claudio Macci , Barbara Pacchiarotti

We consider a general class of statistical mechanical models of coherent structures in turbulence, which includes models of two-dimensional fluid motion, quasi-geostrophic flows, and dispersive waves. First, large deviation principles are…

Probability · Mathematics 2007-05-23 R. S. Ellis , K. Haven , B. Turkington

In this article we establish a large deviation principle for the family {\nu_{\epsilon}:\epsilon \in (0,1)} of distributions of the scaled stochastic processes {P_{-\log\sqrt{\epsilon}}Z_t}_{t\leq 1}, where (Z_t)_{t\in \lbrack 0,1]} is a…

Probability · Mathematics 2009-04-06 Z. Qian , C. Xu

In this work, we establish, for a strong Feller process, the large deviation principle for the occupation measure conditioned not to exit a given subregion. The rate function vanishes only at a unique measure, which is the so-called…

Probability · Mathematics 2024-11-27 Arnaud Guillin , Boris Nectoux , Liming Wu

In this paper we prove a Large Deviation Principle for the sequence of symmetrised empirical measures $\frac{1}{n} \sum_{i=1}^{n} \delta_{(X^n_i,X^n_{\sigma_n(i)})}$ where $\sigma_n$ is a random permutation and $((X_i^n)_{1 \leq i \leq…

Probability · Mathematics 2007-09-13 José Trashorras

We obtain large deviation bounds for the measure of deviation sets associated to asymptotically additive and sub-additive potentials under some weak specification properties. In particular a large deviation principle is obtained in the case…

Dynamical Systems · Mathematics 2019-02-20 Paulo Varandas , Yun Zhao

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

We obtain large deviation results for non-uniformly expanding maps with non-flat singularities or criticalities and for partially hyperbolic non-uniformly expanding attracting sets. That is, given a continuous function we consider its space…

Dynamical Systems · Mathematics 2018-09-14 V Araujo , M J Pacifico

We establish the Level-1 and Level-3 Large Deviation Principles (LDPs) for invariant measures on shift spaces over finite alphabets under very general decoupling conditions for which the thermodynamic formalism does not apply. Such…

Mathematical Physics · Physics 2019-06-28 Noé Cuneo , Vojkan Jakšić , Claude-Alain Pillet , Armen Shirikyan

We prove a full large deviations principle in large time, for a diffusion process with random drift V, which is a centered Gaussian shear flow random field. The large deviations principle is established in a ``quenched'' setting, i.e. is…

Probability · Mathematics 2007-05-23 A. Asselah , F. Castell