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In this short note we consider semi-Markov processes satisfying the condition of direction-time independence (Markov renewal processes). We derive large deviation principles and fluctuation theorems for the empirical current and the…

Statistical Mechanics · Physics 2017-09-19 A. Faggionato

In this paper we establish the large deviation principle for the stochastic quasi-geostrophic equation in the subcritical case with small multiplicative noise. The proof is mainly based on the stochastic control and weak convergence…

Probability · Mathematics 2013-05-22 Wei Liu , Michael Röckner , Xiangchan Zhu

In this article, we prove a joint large deviation principle in $n$ for the \emph{empirical pair measure} and \emph{ empirical offspring measure} of critical multitype Galton-Watson trees conditioned to have exactly $n$ vertices in the weak…

Probability · Mathematics 2017-08-15 Kwabena Doku-Amponsah

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

Given a finite typed rooted tree $T$ with $n$ vertices, the {\em empirical subtree measure} is the uniform measure on the $n$ typed subtrees of $T$ formed by taking all descendants of a single vertex. We prove a large deviation principle in…

Probability · Mathematics 2007-05-23 Amir Dembo , Peter Morters , Scott Sheffield

We study the asymptotic properties, in the weak sense, of regenerative processes and Markov renewal processes. For the latter, we derive both renewal-type results, also concerning the related counting process, and ergodic-type ones,…

Probability · Mathematics 2025-05-20 Andrea Pedicone , Fabrizio Cinque

The limits of scaled relative entropies between probability distributions associated with N-particle weakly interacting Markov processes are considered. The convergence of such scaled relative entropies is established in various settings.…

Probability · Mathematics 2015-02-16 Amarjit Budhiraja , Paul Dupuis , Markus Fischer , Kavita Ramanan

We study large deviation properties of systems of weakly interacting particles modeled by It\^{o} stochastic differential equations (SDEs). It is known under certain conditions that the corresponding sequence of empirical measures…

Probability · Mathematics 2012-09-26 Amarjit Budhiraja , Paul Dupuis , Markus Fischer

For a large class of transitive non-hyperbolic systems, we construct nonhyperbolic ergodic measures with entropy arbitrarily close to its maximal possible value. The systems we consider are partially hyperbolic with one-dimension central…

Dynamical Systems · Mathematics 2022-07-13 Lorenzo J. Díaz , Katrin Gelfert , Michał Rams

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 establish the weak large deviations principle for empirical measures of Markov chains on $\mathbb R^d$ under mild assumptions. In particular, no irreducibility is assumed and the initial measure may be arbitrary. The proof is entirely…

Probability · Mathematics 2026-04-24 Léo Daures

We investigate a Coulomb gas in a potential satisfying a weaker growth assumption than usual and establish a large deviation principle for its empirical measure. As a consequence the empirical measure is seen to converge towards a…

Probability · Mathematics 2012-05-29 Adrien Hardy

In this paper, we prove a large deviation principle for the empirical measures of a system of weakly interacting diffusion with reflection. We adopt the weak convergence approach. To make this approach work, we show that the sequence of…

Probability · Mathematics 2023-04-04 Ping Cheng , Rong Wei , Tusheng Zhang

Consider an intersection measure $\ell_t ^{\mathrm{IS}}$ of $p$ independent (possibly different) $m$-symmetric Hunt processes up to time $t$ in a metric measure space $E$ with a Radon measure $m$. We derive a Donsker-Varadhan type large…

Probability · Mathematics 2018-05-22 Takahiro Mori

We consider a discrete Markov-additive process, that is a Markov chain on a state space $\mathbb{Z}^d \times E$ with invariant jumps along the $\mathbb{Z}^d$ component. In the case where the set $E$ is finite, we derive an asymptotic…

Probability · Mathematics 2026-05-27 Théo Ballu

For suitable families of locally infinitely divisible Markov processes $\{\xi^{{\epsilon}}_t\}_{0\leq t\leq T}$ with frequent small jumps depending on a small parameter $\epsilon>0,$ precise asymptotics for large deviations of integral…

Probability · Mathematics 2012-11-27 Xiangfeng Yang

We consider periodic Markov chains with absorption. Applying to iterates of this periodic Markov chain criteria for the exponential convergence of conditional distributions of aperiodic absorbed Markov chains, we obtain exponential…

Probability · Mathematics 2022-11-08 Nicolas Champagnat , Denis Villemonais

Here we propose the Donsker-Varadhan-type compactness conditions and prove the joint large deviation principle for the empirical measure and empirical flow of Markov renewal processes (semi-Markov processes) with a countable state space,…

Probability · Mathematics 2022-10-27 Chen Jia , Da-quan Jiang , Bingjie Wu

The classical Donsker weak invariance principle is extended to a Besov spaces framework. Polygonal line processes build from partial sums of stationary martingale differences as well independent and identically distributed random variables…

Probability · Mathematics 2020-03-10 Davide Giraudo , Alfredas Rackauskas

Strong invariance principles describe the error term of a Brownian approximation of the partial sums of a stochastic process. While these strong approximation results have many applications, the results for continuous-time settings have…

Statistics Theory · Mathematics 2022-06-17 Ardjen Pengel , Joris Bierkens
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