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We consider a diffusion given by a small noise perturbation of a dynamical system driven by a potential function with a finite number of local minima. The classical results of Freidlin and Wentzell show that the time this diffusion spends…

Probability · Mathematics 2021-01-20 Thomas G. Kurtz , Jason Swanson

In this work we present a coupled-cluster theory for the propagation of multireference electronic systems initiating at general quantum mechanical states. Our formalism is based on the infinitesimal analysis of modified cluster operators,…

Chemical Physics · Physics 2025-05-09 Martín A. Mosquera

A labelled Markov process (LMP) consists of a measurable space $S$ together with an indexed family of Markov kernels from $S$ to itself. This structure has been used to model probabilistic computations in Computer Science, and one of the…

Probability · Mathematics 2023-06-22 Jan Pachl , Pedro Sánchez Terraf

Changing time of simple continuous-time Markov counting processes by independent unit-rate Poisson processes results in Markov counting processes for which we provide closed-form transition rates via composition of trajectories and with…

Probability · Mathematics 2014-03-25 Carles Bretó

We develop Markov chain mixing time estimates for a class of Markov chains with restricted transitions. We assume transitions may occur along a cycle of $n$ nodes and on $n^\gamma$ additional edges, where $\gamma < 1$. We find that the…

Probability · Mathematics 2015-06-26 Balázs Gerencsér

A labelled Markov decision process is a labelled Markov chain with nondeterminism, i.e., together with a strategy a labelled MDP induces a labelled Markov chain. The model is related to interval Markov chains. Motivated by applications of…

Formal Languages and Automata Theory · Computer Science 2020-09-25 Stefan Kiefer , Qiyi Tang

We prove that the probability substitution matrices obtained from a continuous-time Markov chain form a multiplicatively closed set if and only if the rate matrices associated to the chain form a linear space spanning a Lie algebra. The key…

Group Theory · Mathematics 2017-09-04 Jeremy G Sumner

Conditionally Markov (CM) sequences are powerful mathematical tools for modeling random phenomena. There are several classes of CM sequences one of which is the reciprocal sequence. Reciprocal sequences have been widely used in many areas…

Probability · Mathematics 2021-03-16 Reza Rezaie , X. Rong Li

In this paper, we present a new, optimization-based method to exhibit cyclic behavior in non-reversible stochastic processes. While our method is general, it is strongly motivated by discrete simulations of ordinary differential equations…

Data Structures and Algorithms · Computer Science 2016-09-12 Isabel Beckenbach , Leon Eifler , Konstantin Fackeldey , Ambros Gleixner , Andreas Grever , Marcus Weber , Jakob Witzig

Processes having the same bridges are said to belong to the same reciprocal class. In this article we analyze reciprocal classes of Markov counting processes by identifying their reciprocal invariants and we characterize them as the set of…

Probability · Mathematics 2022-09-05 Giovanni Conforti , Christian Léonard , Rüdiger Murr , Sylvie Roelly

Proposed is an alternative method for permutational sampling in quantum gases using the path integral formulation of statistical mechanics. It is shown that in principle we are able to use two operators which enable us to construct a Markov…

Statistical Mechanics · Physics 2009-11-13 Ryan Springall , Manolo Per , Ian K. Snook

Real causal processes may contain feedback loops and change over time. In this paper, we model cycles and non-stationary distributions using a mixture of directed acyclic graphs (DAGs). We then study the conditional independence (CI)…

Statistics Theory · Mathematics 2019-09-16 Eric V. Strobl

A theory of systems with long-range correlations based on the consideration of binary N-step Markov chains is developed. In our model, the conditional probability that the i-th symbol in the chain equals zero (or unity) is a linear function…

Data Analysis, Statistics and Probability · Physics 2007-05-23 O. V. Usatenko , V. A. Yampol'skii

We prove generalizations of the first and second Ray-Knight theorems, for a large class of non-symmetric strong Markov processes. These results link the local times of the Markov process with the squares of associated Gaussian processes.…

Probability · Mathematics 2026-02-20 P. J. Fitzsimmons , Jay Rosen

In this paper, we study darning of general symmetric Markov processes by shorting some parts of the state space into singletons. A natural way to construct such processes is via Dirichlet forms restricted to the function space whose members…

Probability · Mathematics 2017-02-08 Zhen-Qing Chen , Jun Peng

Switching dynamical systems are an expressive model class for the analysis of time-series data. As in many fields within the natural and engineering sciences, the systems under study typically evolve continuously in time, it is natural to…

Machine Learning · Computer Science 2022-05-19 Lukas Köhs , Bastian Alt , Heinz Koeppl

We introduce a new embarrassingly parallel parameter learning algorithm for Markov random fields with untied parameters which is efficient for a large class of practical models. Our algorithm parallelizes naturally over cliques and, for…

Machine Learning · Statistics 2014-02-06 Yariv Dror Mizrahi , Misha Denil , Nando de Freitas

To provide a more accurate description of the driving behaviors in vehicle queues, a namely Markov-Gap cellular automata model is proposed in this paper. It views the variation of the gap between two consequent vehicles as a Markov process…

Data Analysis, Statistics and Probability · Physics 2009-04-23 Fa Wang , Li Li , Jianming Hu , Yan Ji , Danya Yao , Yi Zhang , Xuexiang Jin , Yuelong Su , Zheng Wei

Time-reversal symmetry is a prevalent feature of microscopic physics, including operational quantum theory and classical general relativity. Previous works have studied indefinite causal structure using the language of operational quantum…

Quantum Physics · Physics 2024-06-27 Luke Mrini , Lucien Hardy

We prove a law of large numbers for empirical approximations of the spectrum of a kernel integral operator by the spectrum of random matrices based on a sample drawn from a Markov chain, which complements the results by V. Koltchinskii and…

Probability · Mathematics 2015-09-21 Radosław Adamczak , Witold Bednorz
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