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In this paper we study the asymptotic behavior of linear processes having as innovations mean zero, square integrable functions of stationary reversible Markov chains. In doing so we shall preserve the generality of coefficients assuming…

Probability · Mathematics 2012-06-05 Magda Peligrad

The cutoff phenomenon is an abrupt transition from out of equilibrium to equilibrium undergone by certain Markov processes in the limit where the size of the state space tends to infinity: instead of decaying gradually over time, their…

Probability · Mathematics 2025-08-29 Justin Salez

In this second part, we analyze the dissipation properties of Generalized Poisson-Kac (GPK) processes, considering the decay of suitable $L^2$-norms and the definition of entropy functions. In both cases, consistent energy dissipation and…

Statistical Mechanics · Physics 2017-08-02 Massimiliano Giona , Antonio Brasiello , Silvestro Crescitelli

We present a general approach for computing the dynamic partition function of a continuous-time Markov process. The Ruelle topological pressure is identified with the large deviation function of a physical observable. We construct for the…

Statistical Mechanics · Physics 2010-05-11 Vivien Lecomte , Cecile Appert-Rolland , Frederic van Wijland

In his 2011 work, Maas has shown that the law of any time-reversible continuous-time Markov chain with finite state space evolves like a gradient flow of the relative entropy with respect to its stationary distribution. In this work we show…

Probability · Mathematics 2015-04-03 Helge Dietert

Entropy is a classical measure to quantify the amount of information or complexity of a system. Various entropy-based measures such as functional and spectral entropies have been proposed in brain network analysis. However, they are less…

Neurons and Cognition · Quantitative Biology 2018-03-08 Hyekyoung Lee , Eunkyung Kim , Hyejin Kang , Youngmin Huh , Youngjo Lee , Seonhee Lim , Dong Soo Lee

In this work we investigate the long-time behavior, that is the existence and characterization of invariant measures as well as convergence of transition probabilities, for Markov processes obtained as the unique mild solution to stochastic…

Probability · Mathematics 2022-03-17 Balint Fárkas , Martin Friesen , Barbara Rüdiger , Dennis Schroers

In this paper, we seek to understand the behavior of dynamical systems that are perturbed by a parameter that changes discretely in time. If we impose certain conditions, we can study certain embedded systems within a hybrid system as…

Dynamical Systems · Mathematics 2014-08-04 Xavier Garcia , Jennifer Kunze , Thomas Rudelius , Anthony Sanchez , Sijing Shao , Emily Speranza , Chad Vidden

An important problem in applied dynamical systems is to compute the external forcing that provokes the largest response of a desired observable quantity. For this, we investigate the perturbation theory of Markov matrices in connection with…

Dynamical Systems · Mathematics 2025-07-21 Manuel Santos Gutierrez , Niccolo Zagli , Giulia Carigi

This note develops shortly the theory of time-inhomogeneous additive functionals and is a useful support for the analysis of time-dependent Markov processes and related topics. It is a significant tool for the analysis of BSDEs in law. In…

Probability · Mathematics 2017-08-21 Adrien Barrasso , Francesco Russo

This paper contributes an in-depth study of properties of continuous time Markov chains (CTMCs) on non-negative integer lattices $\N_0^d$, with particular interest in one-dimensional CTMCs with polynomial transitions rates. Such stochastic…

Probability · Mathematics 2020-06-22 Chuang Xu , Mads Christian Hansen , Carsten Wiuf

We formalize and analyze the notions of stochastic monotonicity and realizable mono-tonicity for Markov Chains in continuous-time, taking values in a finite partially ordered set. Similarly to what happens in discrete-time, the two notions…

Probability · Mathematics 2016-03-08 Paolo Dai Pra , Pierre-Yves Louis , Ida Minelli

How is it that entropy derivatives almost in their own are characterizing the state of a system close to equilibrium, and what happens further away from it? We explain within the framework of Markov jump processes why fluctuation theory can…

Statistical Mechanics · Physics 2009-08-24 Christian Maes , Karel Netočný , Bram Wynants

Sofic entropy is an invariant for probability-preserving actions of sofic groups. It was introduced a few years ago by Lewis Bowen, and shown to extend the classical Kolmogorov-Sinai entropy from the setting of amenable groups. Some parts…

Dynamical Systems · Mathematics 2016-06-14 Tim Austin

It is well-known that compositions of Markov processes with inverse subordinators are governed by integro-differential equations of generalized fractional type. This kind of processes are of wide interest in statistical physics as they are…

Probability · Mathematics 2020-05-13 Luisa Beghin , Claudio Macci , Costantino Ricciuti

This work focuses on off-policy evaluation (OPE) with function approximation in infinite-horizon undiscounted Markov decision processes (MDPs). For MDPs that are ergodic and linear (i.e. where rewards and dynamics are linear in some known…

Machine Learning · Computer Science 2020-06-24 Nevena Lazic , Dong Yin , Mehrdad Farajtabar , Nir Levine , Dilan Gorur , Chris Harris , Dale Schuurmans

The minimum entropy production principle provides an approximative variational characterization of close-to-equilibrium stationary states, both for macroscopic systems and for stochastic models. Analyzing the fluctuations of the empirical…

Mathematical Physics · Physics 2009-11-05 C. Maes , K. Netocny

\noindent Consider an infinite collection of particles on the real line moving according to independent Brownian motions and such that the $i$-th particle from the left gets the drift $g_{i-1}$. The case where $g_0=1$ and $g_{i}=0$ for all…

Probability · Mathematics 2024-07-09 Sayan Banerjee , Amarjit Budhiraja

The aim of this survey is to present the main important techniques and tools from variational analysis used for first and second order dynamical systems of implicit type for solving monotone inclusions and non-smooth optimization problems.…

Optimization and Control · Mathematics 2020-07-02 Ernö Robert Csetnek

Consider the continuous-time Markov Branching Process. In critical case we consider a situation when the generating function of intensity of transformation of particles has the infinite second moment, but its tail regularly varies in sense…

Probability · Mathematics 2022-01-07 Azam Imomov
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