English
Related papers

Related papers: Large deviations asymptotics and the spectral theo…

200 papers

Discrete stationary classical processes as well as quantum lattice states are asymptotically confined to their respective typical support, the exponential growth rate of which is given by the (maximal ergodic) entropy. In the iid case the…

Probability · Mathematics 2009-11-13 I. Bjelakovic , J. -D. Deuschel , T. Krueger , R. Seiler , Ra. Siegmund-Schultze , A. Szkola

This paper is devoted to the analysis of the finite-dimensional distributions and asymptotic behavior of extremal Markov processes connected to the Kendall convolution. In particular, based on its stochastic representation, we provide…

Probability · Mathematics 2019-10-10 Marek Arendarczyk , Barbara Jasiulis-Gołdyn , Edward Omey

Moderate deviation principles for empirical measure processes associated with weakly interacting Markov processes are established. Two families of models are considered: the first corresponds to a system of interacting diffusions whereas…

Probability · Mathematics 2015-10-09 Amarjit Budhiraja , Ruoyu Wu

We prove a sample path large deviation principle (LDP) with sub-linear speed for unbounded functionals of certain Markov chains induced by the Lindley recursion. The LDP holds in the Skorokhod space $\mathbb{D}[0,T]$ equipped with the…

Probability · Mathematics 2023-10-03 Mihail Bazhba , Jose Blanchet , Chang-Han Rhee , Bert Zwart

We consider two approaches to study non-reversible Markov processes, namely the Hypocoercivity Theory (HT) and GENERIC (General Equations for Non-Equilibrium Reversible-Irreversible Coupling); the basic idea behind both of them is to split…

Probability · Mathematics 2023-01-25 Manh Hong Duong , Michela Ottobre

We consider random walk with bounded jumps on a hypercubic lattice of arbitrary dimension in a dynamic random environment. The environment is temporally independent and spatially translation invariant. We study the rate functions of the…

Probability · Mathematics 2016-07-26 Firas Rassoul-Agha , Timo Seppäläinen , Atilla Yilmaz

The continuous time Markov process considered in this paper belongs to a class of population models with linear growth and catastrophes. There, the catastrophes happen at the arrival times of a Poisson process, and at each catastrophe time,…

Probability · Mathematics 2019-05-14 A. Logachov , O. Logachova , A. Yambartsev

We establish large deviation principles for the couple of the maximum likelihood estimators of dimensional and drift coefficients in the generalised squared radial Ornstein-Uhlenbeck process. We focus our attention to the most tractable…

Probability · Mathematics 2016-11-28 Marie du Roy de Chaumaray

We prove pathwise large-deviation principles of switching Markov processes by exploiting the connection to associated Hamilton-Jacobi equations, following Jin Feng's and Thomas Kurtz's method. In the limit that we consider, we show how the…

Probability · Mathematics 2021-06-08 Mark A. Peletier , Mikola C. Schlottke

We study large deviations asymptotics for a class of unbounded additive functionals, interpreted as normalized accumulated areas, of one-dimensional Langevin diffusions with sub-linear gradient drifts. Our results provide parametric…

Probability · Mathematics 2023-10-23 Mihail Bazhba , Jose Blanchet , Roger J. A. Laeven , Bert Zwart

Let $X$ be a L\'evy process with regularly varying L\'evy measure $\nu$. We obtain sample-path large deviations for scaled processes $\bar X_n(t) \triangleq X(nt)/n$ and obtain a similar result for random walks. Our results yield detailed…

Probability · Mathematics 2017-12-12 Chang-Han Rhee , Jose Blanchet , Bert Zwart

We prove existence of invariant measures for the Markovian semigroup generated by the solution to a parabolic semilinear stochastic PDE whose nonlinear drift term satisfies only a kind of symmetry condition on its behavior at infinity, but…

Analysis of PDEs · Mathematics 2020-04-21 Carlo Marinelli , Luca Scarpa

The asymptotic analysis of a class of stochastic partial differential equations (SPDEs) with fully locally monotone coefficients covering a large variety of physical systems, a wide class of quasilinear SPDEs and a good number of fluid…

Probability · Mathematics 2022-12-13 Ankit Kumar , Manil T. Mohan

We study spectral problems for integro-differential equations arising in the theory of Gaussian processes similar to the fractional Brownian motion. We generalize the method of Chigansky--Kleptsyna and obtain the two-term eigenvalue…

Spectral Theory · Mathematics 2020-04-07 Alexander I. Nazarov

Probabilistic solutions of the so called Schr\"{o}dinger boundary data problem provide for a unique Markovian interpolation between any two strictly positive probability densities designed to form the input-output statistics data for the…

Quantum Physics · Physics 2009-10-28 Piotr Garbaczewski , Robert Olkiewicz

It is known that state-dependent, multi-step Lyapunov bounds lead to greatly simplified verification theorems for stability for large classes of Markov chain models. This is one component of the "fluid model" approach to stability of…

Optimization and Control · Mathematics 2012-05-18 Serdar Yüksel , Sean P. Meyn

We construct and study branching Markov processes on the space of finite configurations of the state space of a given standard process, controlled by a branching kernel and a killing one. In particular, we may start with a superprocess,…

Probability · Mathematics 2015-08-03 Lucian Beznea , Oana Lupascu

We consider the Markov renewal equation $F(t) = f(t) + \boldsymbol{\mu}*F(t)$ for vector-valued functions $f,F: \mathbb{R} \to \mathbb{R}^{p}$ and a $p \times p$ matrix $\boldsymbol{\mu}$ of locally finite measures $\mu^{i,j}$ on…

Probability · Mathematics 2025-03-10 Konrad Kolesko , Matthias Meiners , Ivana Tomic

We address the general problem of formulating the dynamical large deviations of non-Markovian systems in a closed form. Specifically, we consider a broad class of ``self-interacting'' jump processes whose dynamics depends on the past…

Statistical Mechanics · Physics 2026-03-25 Francesco Coghi , Amarjit Budhiraja , Juan P. Garrahan

This paper studies the asymptotic behavior of several central objects in Dunkl theory as the dimension of the underlying space grows large. Our starting point is the observation that a recent result from the random matrix theory literature…

Probability · Mathematics 2023-05-24 Jiaoyang Huang , Colin McSwiggen
‹ Prev 1 8 9 10 Next ›