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Related papers: A large-deviation view on dynamical Gibbs-non-Gibb…

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The theory of large deviations has been applied successfully in the last 30 years or so to study the properties of equilibrium systems and to put the foundations of equilibrium statistical mechanics on a clearer and more rigorous footing. A…

Statistical Mechanics · Physics 2018-09-14 Hugo Touchette , Rosemary J. Harris

Large random matrices appear in different fields of mathematics and physics such as combinatorics, probability theory, statistics, operator theory, number theory, quantum field theory, string theory etc... In the last ten years, they…

Probability · Mathematics 2007-05-23 Alice Guionnet

Let $A$ be a transition probability kernel on a finite state space $\Delta^o =\{1, \ldots , d\}$ such that $A(x,y)>0$ for all $x,y \in \Delta^o$. Consider a reinforced chain given as a sequence $\{X_n, \; n \in \mathbb{N}_0\}$ of…

Probability · Mathematics 2022-05-20 Amarjit Budhiraja , Adam Waterbury

This paper is devoted to the problem of sample path large deviations for the Markov processes on R_+^N having a constant but different transition mechanism on each boundary set {x:x_i=0 for i\notin\Lambda, x_i>0 for i\in\Lambda}. The global…

Probability · Mathematics 2007-05-23 Irina Ignatiouk-Robert

We consider discrete-time Markov chains and study large deviations of the pair empirical occupation measure, which is useful to compute fluctuations of pure-additive and jump-type observables. We provide an exact expression for the…

Statistical Mechanics · Physics 2022-07-04 Giorgio Carugno , Pierpaolo Vivo , Francesco Coghi

We show that a collection of independent Ising spins evolving stochastically can display surprisingly large fluctuations towards ordered behaviour, as quantified by certain types of time-integrated plaquette observables, despite the…

Statistical Mechanics · Physics 2020-04-22 Loredana M. Vasiloiu , Tom H. E. Oakes , Federico Carollo , Juan P. Garrahan

When analysing statistical systems or stochastic processes, it is often interesting to ask how they behave given that some observable takes some prescribed value. This conditioning problem is well understood within the linear operator…

Statistical Mechanics · Physics 2022-03-09 Lydia Chabane , Alexandre Lazarescu , Gatien Verley

Macroscopic fluctuation theory has shown that a wide class of non-equilibrium stochastic dynamical systems obey a large deviation principle, but except for a few one-dimensional examples these large deviation principles are in general not…

Statistical Mechanics · Physics 2014-10-02 Gino Del Ferraro , Erik Aurell

The theory of large deviations deals with the probabilities of rare events (or fluctuations) that are exponentially small as a function of some parameter, e.g., the number of random components of a system, the time over which a stochastic…

Statistical Mechanics · Physics 2012-03-01 Hugo Touchette

The study of chaotic systems, where rare events play a pivotal role, is essential for understanding complex dynamics due to their sensitivity to initial conditions. Recently, tools from large deviation theory, typically applied in the…

Chaotic Dynamics · Physics 2026-05-06 Lucianno Defaveri , Naftali R. Smith

We study using large deviation theory the fluctuations of time-integrated functionals or observables of the unbiased random walk evolving on Erd\"os-R\'enyi random graphs, and construct a modified, biased random walk that explains how these…

Statistical Mechanics · Physics 2019-03-06 Francesco Coghi , Jules Morand , Hugo Touchette

We investigate piecewise-linear stochastic models as with regards to the probability distribution of functionals of the stochastic processes, a question which occurs frequently in large deviation theory. The functionals that we are looking…

Statistical Mechanics · Physics 2015-06-22 Yaming Chen , Wolfram Just

We study the large deviation function for the entropy production rate in two driven one-dimensional systems: the asymmetric random walk on a discrete lattice and Brownian motion in a continuous periodic potential. We compare two approaches:…

Statistical Mechanics · Physics 2013-01-21 Thomas Speck , Andreas Engel , Udo Seifert

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

We prove a large deviation principle on path space for a class of discrete time Markov processes whose state space is the intersection of a regular domain $\L\subset \R^d$ with some lattice of spacing $\e$. Transitions from $x$ to $y$ are…

Probability · Mathematics 2007-05-23 Anton Bovier , Veronique Gayrard

The theory of quantum jump trajectories provides a new framework for understanding dynamical phase transitions in open systems. A candidate for such transitions is the atom maser, which for certain parameters exhibits strong intermittency…

Quantum Physics · Physics 2024-06-19 Federico Girotti , Merlijn van Horssen , Raffaella Carbone , Madalin Guta

We study supercritical branching processes in which all particles evolve according to some general Markovian motion (which may possess absorbing states) and branch independently at a fixed constant rate. Under fairly natural assumptions on…

Probability · Mathematics 2017-07-05 Matthieu Jonckheere , Santiago Saglietti

Consider a large system of $N$ Brownian motions in $\mathbb{R}^d$ with some non-degenerate initial measure on some fixed time interval $[0,\beta]$ with symmetrised initial-terminal condition. That is, for any $i$, the terminal location of…

Probability · Mathematics 2007-05-23 Stefan Adams , Wolfgang König

We consider the Curie-Weiss Widom-Rowlinson model for particles with spins and holes, with a repulsion strength beta between particles of opposite spins. We provide a closed solution of the model, and investigate dynamical Gibbs-non-Gibbs…

Probability · Mathematics 2018-10-01 Sascha Kissel , Christof Kuelske

In a series of two papers, we investigate the large deviations and asymptotic behavior of stochastic models of brain neural networks with random interaction coefficients. In this first paper, we take into account the spatial structure of…

Probability · Mathematics 2017-01-05 Tanguy Cabana , Jonathan Touboul