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The entropy production rate is a central quantity in non-equilibrium statistical physics, scoring how far a stochastic process is from being time-reversible. In this paper, we compute the entropy production of diffusion processes at…

Statistical Mechanics · Physics 2023-06-19 Lancelot Da Costa , Grigorios A. Pavliotis

Markovian intertwining relations between two Markov semigroups are related to the partial inclusion of the spectra of their generators, at least for finite ergodic processes. We check the limitations of this observation by investigating the…

Probability · Mathematics 2019-04-25 Laurent Miclo , Pierre Patie

In this paper we consider an Ornstein-Uhlenbeck (OU) process $(M(t))_{t\geqslant 0}$ whose parameters are determined by an external Markov process $(X(t))_{t\geqslant 0}$ on a finite state space $\{1,\ldots,d\}$; this process is usually…

Probability · Mathematics 2024-06-06 Gang Huang , Marijn Jansen , Michel Mandjes , Peter Spreij , Koen De Turck

This paper studies the asymptotic behavior of processes with switching. More precisely, the stability under fast switching for diffusion processes and discrete state space Markovian processes is considered. The proofs are based on…

Probability · Mathematics 2017-07-07 Sören Christensen , Albrecht Irle

The Ehrenfest time scale in quantum transport separates essentially classical propagation from wave interference and here we consider its effect on the transmission and reflection through quantum dots. In particular we calculate the…

Chaotic Dynamics · Physics 2015-03-17 Daniel Waltner , Jack Kuipers

We propose a class of non-Markov population models with continuous or discrete state space via a limiting procedure involving sequences of rescaled and randomly time-changed Galton--Watson processes. The class includes as specific cases the…

Probability · Mathematics 2021-01-12 Luisa Andreis , Federico Polito , Laura Sacerdote

Transport properties of open chaotic ballistic systems and their statistics can be expressed in terms of the scattering matrix connecting incoming and outgoing wavefunctions. Here we calculate the dependence of correlation functions of…

Mesoscale and Nanoscale Physics · Physics 2015-05-19 Daniel Waltner , Jack Kuipers , Klaus Richter

ODE solvers with randomly sampled timestep sizes appear in the context of chaotic dynamical systems, differential equations with low regularity, and, implicitly, in stochastic optimisation. In this work, we propose and study the stochastic…

Numerical Analysis · Mathematics 2024-08-05 Jonas Latz

Oscillatory systems of interacting Hawkes processes with Erlang memory kernels were introduced in Ditlevsen (2017). They are piecewise deterministic Markov processes (PDMP) and can be approximated by a stochastic diffusion. First, a strong…

Numerical Analysis · Mathematics 2020-03-25 Julien Chevallier , Anna Melnykova , Irene Tubikanec

Motivated by applications to mathematical biology, we study the averaging problem for slow-fast systems, {\em in the case in which the fast dynamics is a stochastic process with multiple invariant measures}. We consider both the case in…

Probability · Mathematics 2023-08-17 B. D. Goddard , M. Ottobre , K. J. Painter , I. Souttar

The aim of this paper is to study the asymptotic behavior of a system of birth and death processes in mean field type interaction in discrete space. We first establish the exponential convergence of the particle system to equilibrium for a…

Probability · Mathematics 2015-10-13 Marie-Noémie Thai

We consider a time-inhomogeneous diffusion process able to describe the dynamics of infected people in a susceptible-infectious epidemic model in which the transmission intensity function is time-dependent. Such a model is well suited to…

Methodology · Statistics 2024-10-30 Giuseppina Albano , Virginia Giorno , Francisco Torres-Ruiz

We propose and investigate a method for identifying timescales of dissipation in nonequilibrium steady states modeled as discrete-state Markov jump processes. The method is based on how the irreversibility-measured by the statistical…

Statistical Mechanics · Physics 2023-07-24 Freddy A. Cisneros , Nikta Fakhri , Jordan M. Horowitz

Stochastic convergence of discrete time Markov processes has been analysed based on a dual Lyapunov approach. Using some existing results on ergodic theory of Markov processes, it has been shown that existence of a properly subinvariant…

Dynamical Systems · Mathematics 2024-02-20 Özkan Karabacak , Horia Cornean , Rafael Wisniewski

We investigate the problem of minimizing the entropy production for a physical process that can be described in terms of a Markov jump dynamics. We show that, without any further constraints, a given time-evolution may be realized at…

Statistical Mechanics · Physics 2022-02-16 Andreas Dechant

This paper deals with the realisation of affine constraints on nonreversible stochastic differential equations (SDE) by strong confining forces. We prove that the confined dynamics converges pathwise and on bounded time intervals to the…

Probability · Mathematics 2025-05-02 Carsten Hartmann , Lara Neureither , Upanshu Sharma

The definition of a consistent evolution equation for statistical hybrid quantum-classical systems is still an open problem. In this paper we analyze the case of Ehrenfest dynamics on systems defined by a probability density and identify…

Quantum Physics · Physics 2023-08-30 J. L. Alonso , C. Bouthelier-Madre , J. Clemente-Gallardo , D. Martínez-Crespo , J. Pomar

We propose a discrete time discrete space Markov chain approximation with a Brownian bridge correction for computing curvilinear boundary crossing probabilities of a general diffusion process on a finite time interval. For broad classes of…

Probability · Mathematics 2021-12-13 Vincent Liang , Konstantin Borovkov

An Ornstein-Uhlenbeck (OU) process can be considered as a continuous time interpolation of the discrete time AR$(1)$ process. Departing from this fact, we analyse in this work the effect of iterating OU treated as a linear operator that…

Statistics Theory · Mathematics 2012-10-02 Argimiro Arratia , Alejandra Cabaña , Enrique M. Cabaña

Hypergraphs model higher-order interactions, but realistic hypergraph generation remains difficult because incidence, hyperedge-size heterogeneity, and overlap structure are not faithfully captured by pairwise reductions. We propose \HEDGE,…

Machine Learning · Statistics 2026-05-07 Christopher Nemeth
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