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A reaction network is a chemical system involving multiple reactions and chemical species. Stochastic models of such networks treat the system as a continuous time Markov chain on the number of molecules of each species with reactions as…

Probability · Mathematics 2007-05-23 Karen Ball , Thomas G. Kurtz , Lea Popovic , Greg Rempala

We consider continuous-time Markov chains which display a family of wells at the same depth. We provide sufficient conditions which entail the convergence of the finite-dimensional distributions of the order parameter to the ones of a…

Probability · Mathematics 2019-10-03 Claudio Landim , Michail Loulakis , Mustapha Mourragui

The paper is devoted to studies of perturbed Markov chains commonly used for description of information networks. In such models, the matrix of transition probabilities for the corresponding Markov chain is usually regularised by adding a…

Transfer entropy is used to establish a measure of causal relationships between two variables. Symbolic transfer entropy, as an estimation method for transfer entropy, is widely applied due to its robustness against non-stationarity. This…

Computational Complexity · Computer Science 2024-09-24 Dian Jin

In this article almost semi-continuous processes with stationary independent increments on a finite irreducible Markov chain are considered. For these processes the components of matrix factorization identity are concretely defined. On the…

Probability · Mathematics 2009-09-01 D. V. Gusak , E. V. Karnaukh

We study the problem of learning the transition matrices of a set of Markov chains from a single stream of observations on each chain. We assume that the Markov chains are ergodic but otherwise unknown. The learner can sample Markov chains…

Machine Learning · Computer Science 2019-11-14 Mohammad Sadegh Talebi , Odalric-Ambrym Maillard

Applications of stochastic models often involve the evaluation of steady-state performance, which requires solving a set of balance equations. In most cases of interest, the number of equations is infinite or even uncountable. As a result,…

Optimization and Control · Mathematics 2022-04-08 Shukai Li , Sanjay Mehrotra

We obtain universal estimates on the convergence to equilibrium and the times of coupling for continuous time irreducible reversible finite-state Markov chains, both in the total variation and in the L^2 norms. The estimates in total…

Probability · Mathematics 2012-01-24 Mykhaylo Shkolnikov

We establish the existence and uniqueness of quasi-stationary and quasi-ergodic measures for almost surely absorbed discrete-time Markov chains under weak conditions. We obtain our results by exploiting Banach lattice properties of…

It is shown that the combinatorics of commutation relations is well suited for analyzing the convergence rate of certain Markov chains. Examples studied include random walk on irreducible representations, a local random walk on partitions…

Probability · Mathematics 2008-01-21 Jason Fulman

Transfer entropy is a measure of the magnitude and the direction of information flow between jointly distributed stochastic processes. In recent years, its permutation analogues are considered in the literature to estimate the transfer…

Chaotic Dynamics · Physics 2013-03-12 Taichi Haruna , Kohei Nakajima

Using random matrix techniques and the theory of Matrix Product States we show that reduced density matrices of quantum spin chains have generically maximum entropy.

Quantum Physics · Physics 2019-02-27 Benoit Collins , Carlos E. Gonzalez-Guillen , David Perez-Garcia

We investigate the mixing properties of a finite Markov chain in random environment defined as a mixture of a deterministic chain and a chain whose state space has been permuted uniformly at random. This work is the counterpart of a…

Probability · Mathematics 2024-02-07 Bastien Dubail

We characterize absorption-time distributions for birth-death Markov chains with an absorbing boundary. For "extinction-prone" chains (which drift on average toward the absorbing state) the asymptotic distribution is Gaussian, Gumbel, or…

Statistical Mechanics · Physics 2022-06-08 David Hathcock , Steven H. Strogatz

We consider the problem of approximating the stationary distribution of an ergodic Markov chain given a set of sampled transitions. Classical simulation-based approaches assume access to the underlying process so that trajectories of…

Machine Learning · Computer Science 2020-03-03 Junfeng Wen , Bo Dai , Lihong Li , Dale Schuurmans

We analyse the structure of imprecise Markov chains and study their convergence by means of accessibility relations. We first identify the sets of states, so-called minimal permanent classes, that are the minimal sets capable of containing…

Probability · Mathematics 2016-09-20 Damjan Skulj

The inference of thermodynamic quantities from the description of an only partially accessible physical system is a central challenge in stochastic thermodynamics. A common approach is coarse-graining, which maps the dynamics of such a…

Statistical Mechanics · Physics 2022-08-19 Jann van der Meer , Benjamin Ertel , Udo Seifert

We give computable bounds on the rate of convergence of the transition probabilities to the stationary distribution for a certain class of geometrically ergodic Markov chains. Our results are different from earlier estimates of Meyn and…

Probability · Mathematics 2007-05-23 Peter H. Baxendale

In this didactical note I review in depth the rationale for using generalised canonical distributions in quantum statistics. Particular attention is paid to the proper definitions of quantum entropy and quantum relative entropy, as well as…

Quantum Physics · Physics 2008-06-03 Jochen Rau

In this paper, we continue the investigation of quantum Markov states (QMS) and define their mean entropies. Such entropies are explicitly computed under certain conditions. The present work takes a huge leap forward at tackling one of the…

Mathematical Physics · Physics 2022-09-28 Farrukh Mukhamedov , Abdessatar Souissi
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