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We consider a class of semi-Markov processes (SMP) such that the embedded discrete time Markov chain may be non-homogeneous. The corresponding augmented processes are represented as semi-martingales using stochastic integral equation…

Probability · Mathematics 2022-07-14 Anindya Goswami , Subhamay Saha , Ravishankar Kapildev Yadav

Semi-Markov processes are Markovian processes in which the firing time of the transitions is modelled by probabilistic distributions over positive reals interpreted as the probability of firing a transition at a certain moment in time. In…

Formal Languages and Automata Theory · Computer Science 2017-12-04 Mathias Ruggaard Pedersen , Nathanaël Fijalkow , Giorgio Bacci , Kim Guldstrand Larsen , Radu Mardare

There is a relation between the irreversibility of thermodynamic processes as expressed by the breaking of time-reversal symmetry, and the entropy production in such processes. We explain on an elementary mathematical level the relations…

Statistical Mechanics · Physics 2007-05-23 C. Maes , K. Netocny

We propose a unified framework that extends the inference methods for classical hidden Markov models to continuous settings, where both the hidden states and observations occur in continuous time. Two different settings are analyzed: hidden…

Methodology · Statistics 2021-06-18 Qingcan Wang , Weinan E

We extend the theory of labeled Markov processes with internal nondeterminism, a fundamental concept for the further development of a process theory with abstraction on nondeterministic continuous probabilistic systems. We define…

Logic in Computer Science · Computer Science 2015-03-17 Pedro D'Argenio , Pedro Sánchez Terraf , Nicolás Wolovick

Entropy production (EP) is a central measure in nonequilibrium thermodynamics, as it can quantify the irreversibility of a process as well as its energy dissipation in special cases. Using the time-reversal asymmetry in a system's path…

Statistical Mechanics · Physics 2022-04-26 Dong-Kyum Kim , Sangyun Lee , Hawoong Jeong

Observing stochastic trajectories with rare transitions between states, practically undetectable on time scales accessible to experiments, makes it impossible to directly quantify the entropy production and thus infer whether and how far…

Statistical Mechanics · Physics 2025-12-15 Marco Baiesi , Tomohiro Nishiyama , Gianmaria Falasco

We explore the reflected entropy and the Markov gap between two modes of a free fermionic field as observed by accelerating observers. This is done for both bipartite system which is described by Bell state and tripartite systems which are…

Quantum Physics · Physics 2023-07-03 Jaydeep Kumar Basak , Dimitrios Giataganas , Sayid Mondal , Wen-Yu Wen

A Markov assumption considers a physical system memoryless to simplify its dynamics. Whereas memory effect or the non-Markovian phenomenon is more general in nature. In the quantum regime, it is challenging to define or quantify the…

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

In the general process of eliminating dynamic variables in Markovian models, there exists a difference in the irreversible entropy production between the original and reduced dynamics. We call this difference the hidden entropy production,…

Statistical Mechanics · Physics 2022-06-28 Kyogo Kawaguchi , Yohei Nakayama

We consider the problem of estimating the mean entropy production rate in a nonequilibrium process from the measurements of first-passage quantities associated with a single current. For first-passage processes with large thresholds, Refs.…

Statistical Mechanics · Physics 2025-06-05 Izaak Neri

We propose a compression-based version of the empirical entropy of a finite string over a finite alphabet. Whereas previously one considers the naked entropy of (possibly higher order) Markov processes, we consider the sum of the…

Information Theory · Computer Science 2011-04-05 Paul M. B. Vitányi

Mean-field models are often used to approximate Markov processes with large state-spaces. One-step processes, also known as birth-death processes, are an important class of such processes and are processes with state space…

Dynamical Systems · Mathematics 2015-12-08 Benjamin Armbruster , Ádám Besenyei , Péter L. Simon

In this paper we present elementary computations for some Markov modulated counting processes, also called counting processes with regime switching. Regime switching has become an increasingly popular concept in many branches of science. In…

Probability · Mathematics 2023-02-27 Michel Mandjes , Peter Spreij

We introduce a class of hybrid marked point processes, which encompasses and extends continuous-time Markov chains and Hawkes processes. While this flexible class amalgamates such existing processes, it also contains novel processes with…

Probability · Mathematics 2021-01-06 Maxime Morariu-Patrichi , Mikko S. Pakkanen

Living systems operate far from thermal equilibrium by converting the chemical potential of ATP into mechanical work to achieve growth, replication or locomotion. Given time series observations of intra-, inter- or multicellular processes,…

Biological Physics · Physics 2021-11-03 Dominic J. Skinner , Jörn Dunkel

We show that the dissipation rate bounds the rate at which physical processes can be performed in stochastic systems far from equilibrium. Namely, for rare processes we prove the fundamental tradeoff $\langle \dot S_\text{e} \rangle…

Statistical Mechanics · Physics 2020-09-23 Gianmaria Falasco , Massimiliano Esposito

Systems with interacting degrees of freedom play a prominent role in stochastic thermodynamics. Our aim is to use the concept of detached path probabilities and detached entropy production for bipartite Markov processes and elaborate on a…

Statistical Mechanics · Physics 2017-10-17 Jannik Ehrich , Andreas Engel

This paper considers hidden Markov models where the observations are given as the sum of a latent state which lies in a general state space and some independent noise with unknown distribution. It is shown that these fully nonparametric…

Statistics Theory · Mathematics 2020-01-30 Elisabeth Gassiat , Sylvain Le Corff , Luc Lehéricy
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