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We propose an analytic approach for the steady-state dynamics of Markov processes on locally tree-like graphs. It is based on time-translation invariant probability distributions for edge trajectories, which we encode in terms of infinite…

Statistical Mechanics · Physics 2025-09-08 Stefano Crotti , Thomas Barthel , Alfredo Braunstein

A subdiffusion problem in which the diffusion term is related to a stable stochastic process is introduced. Linear models of these systems have been studied in a general way, but non-linear models require a more specific analysis. The model…

Probability · Mathematics 2021-11-05 Soveny Solís , Vicente Vergara

We consider a discrete time hidden Markov model where the signal is a stationary Markov chain. When conditioned on the observations, the signal is a Markov chain in a random environment under the conditional measure. It is shown that this…

Probability · Mathematics 2009-09-24 Ramon van Handel

In this paper, we consider an integrated MSP-MDP framework which captures features of Markov decision process (MDP) and multistage stochastic programming (MSP). The integrated framework allows one to study a dynamic decision-making process…

Optimization and Control · Mathematics 2025-09-29 Zhiyao Yang , Zhiping Chen , Huifu Xu

This paper investigates the stability of a class of differential systems time-changed by $E_{t}$ which is the inverse of a $\beta$-stable subordinator. In order to explore stability, a time-changed Gronwall's inequality and a generalized…

Probability · Mathematics 2016-02-25 Qiong Wu

We provide a rigorous generalization of the quantum adiabatic theorem for open systems described by a Markovian master equation with time-dependent Liouvillian $\mathcal{L}(t)$. We focus on the finite system case relevant for adiabatic…

Quantum Physics · Physics 2016-03-21 Lorenzo Campos Venuti , Tameem Albash , Daniel A. Lidar , Paolo Zanardi

This paper is concerned with the development of rigorous approximations to various expectations associated with Markov chains and processes having non-stationary transition probabilities. Such non-stationary models arise naturally in…

Probability · Mathematics 2018-05-07 Zeyu Zheng , Harsha Honnappa , Peter W. Glynn

In this work, we study finite-time stability of switched and hybrid systems in the presence of unstable modes. We present sufficient conditions in terms of multiple Lyapunov functions for the origin of the system to be finite time stable.…

Systems and Control · Electrical Eng. & Systems 2024-12-20 Kunal Garg , Dimitra Panagou

The definitions of temporal instability and of spatial instability in a flow system are comparatively surveyed. The simple model of one-dimensional Burgers' flow is taken as the scenario where such different conceptions of instability are…

Fluid Dynamics · Physics 2023-10-04 Antonio Barletta

This paper deals with the problems of stochastic stability and sliding mode control for a class of continuous-time Markovian jump systems with mode-dependent time-varying delays and partly unknown transition probabilities. The design method…

Systems and Control · Computer Science 2018-04-26 Nasibeh Zohrabi , Hasan Zakeri , Amir Hossein Abolmasoumi , Hamid Reza Momeni

A system of metastable plus unstable states is discussed. The mass matrix governing the time development of the system is supposed to vary slowly with time. The adiabatic limit for this case is studied and it is shown that only the…

Atomic Physics · Physics 2008-11-26 Timo Bergmann , Thomas Gasenzer , Otto Nachtmann

In this paper, we obtain some preliminary results on stochastic control theory for time-varying linear systems both continuous and discrete, and further apply to aperiod sample-data linear systems. The Ito's lemma is utilized in this…

Systems and Control · Computer Science 2018-02-27 Chunhe Hu , Dan Wu , Junguo Zhang , Zongji Chen

The elapsed-time model describes the behavior of interconnected neurons through the time since their last spike. It is an age-structured non-linear equation in which age corresponds to the elapsed time since the last discharge, and models…

Dynamical Systems · Mathematics 2025-04-28 María J. Cáceres , José A Cañizo , Nicolas Torres

Recently, Marzlin and Sanders (2004) demonstrated an inconsistency when the adiabatic approximation was applied to specific, "inverse" time-evolving systems. Following that, Tong et al. (2005) showed that the widely used traditional…

Quantum Physics · Physics 2009-11-11 T. Vértesi , R. Englman

We extend the definition of non-adiabatic entropy production given for Markovian systems in [M. Esposito and C. Van den Broeck, Phys. Rev. Lett. 104 090601, (2010)], to arbitrary non-Markov ergodic dynamics. We also introduce a notion of…

Statistical Mechanics · Physics 2012-09-14 Reinaldo García-García

The paper investigates sufficient conditions on a differential inclusion which guarantee that the origin is a finite time stable equilibrium, namely a weak local one, a weak global one or a strong local one. The analysis relies on the…

Optimization and Control · Mathematics 2019-02-22 Radosław Matusik , Andrzej Nowakowski , Sławomir Plaskacz , Andrzej Rogowski

The switch chain is a well-studied Markov chain which can be used to sample approximately uniformly from the set $\Omega(\boldsymbol{d})$ of all graphs with a given degree sequence $\boldsymbol{d}$. Polynomial mixing time (rapid mixing) has…

Combinatorics · Mathematics 2020-12-01 Pu Gao , Catherine Greenhill

This study looks at the finite-dimensional adiabatic evolution influenced by weak perturbations, extending the analysis to the asymptotic time limit. Beginning with the fundamentals of adiabatic transformations and time-dependent effective…

Quantum Physics · Physics 2025-09-05 Zsolt Szabó , Kazuya Yuasa , Daniel Burgarth

We study time-inhomogeneous Markov chains with finite state spaces using Nash and logarithmic-Sobolev inequalities, and the notion of $c$-stability. We develop the basic theory of such functional inequalities in the time-inhomogeneous…

Probability · Mathematics 2011-04-11 L. Saloff-Coste , J. Zúñiga

We say that an algorithm is stable if small changes in the input result in small changes in the output. This kind of algorithm stability is particularly relevant when analyzing and visualizing time-varying data. Stability in general plays…

Data Structures and Algorithms · Computer Science 2025-03-10 Wouter Meulemans , Bettina Speckmann , Kevin Verbeek , Jules Wulms