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The aim of this note is to construct a probability measure on the space of trajectories in a continuous time Markov chain having a finite state diagram, or more generally which admits a global bound on its degree and rates. Our approach is…

Probability · Mathematics 2021-05-25 Michael J. Catanzaro , Vladimir Y. Chernyak , John R. Klein

Variable Length Memory Chains (VLMC), which are generalizations of finite order Markov chains, turn out to be an essential tool to modelize random sequences in many domains, as well as an interesting object in contemporary probability…

Probability · Mathematics 2020-04-20 Peggy Cénac , Brigitte Chauvin , Camille Noûs , Frédéric Paccaut , Nicolas Pouyanne

Quantum walks play an important role in the area of quantum algorithms. Many interesting problems can be reduced to searching marked states in a quantum Markov chain. In this context, the notion of quantum hitting time is very important,…

Quantum Physics · Physics 2009-12-08 R. A. M. Santos , R. Portugal

The dynamics of a quantum system, undergoing unitary evolution and continuous monitoring, can be described in term of quantum trajectories. Although the averaged state fully characterises expectation values, the entire ensamble of…

Quantum Physics · Physics 2023-05-09 Guglielmo Lami , Alessandro Santini , Mario Collura

The possibility of simulating a stochastic process by the intrinsic randomness of quantum system is investigated. Two simulations of Markov Chains by the measurements of quantum systems are proposed.

Mathematical Physics · Physics 2009-09-28 X. F. Liu

A nonlinear Markov chain is a discrete time stochastic process whose transitions depend on both the current state and the current distribution of the process. The nonlinear Markov chain over a infinite state space can be identified by a…

Functional Analysis · Mathematics 2021-08-11 Farrukh Mukhamedov , Otabek Khakimov , Ahmad Fadillah Embong

We study methods of inducing metrics on unital completely positive maps by employing seminorms arising in noncommutative geometry. Our main approach relies on the development of an infinite-dimensional $C^*$-algebraic analogue of the…

Operator Algebras · Mathematics 2026-05-14 Are Austad , Erik Bédos , Jonas Eidesen , Nadia S. Larsen , Tron Omland

Markov chains for probability distributions related to matrix product states and 1D Hamiltonians are introduced. With appropriate 'inverse temperature' schedules, these chains can be combined into a random approximation scheme for ground…

Strongly Correlated Electrons · Physics 2014-05-14 S. Iblisdir

We survey the equations of continuous-time quantum walks on simple one-dimensional lattices, which include the finite and infinite lines and the finite cycle, and compare them with the classical continuous-time Markov chains. The focus of…

Other Condensed Matter · Physics 2007-05-23 D. ben-Avraham , E. Bollt , C. Tamon

In the present paper, we study the continuous-time quantum walk on quotient graphs. On such graphs, there is a straightforward reduction of problem to a subspace that can be considerably smaller than the original one. Along the lines of…

Quantum Physics · Physics 2008-11-23 S. Salimi

This paper presents a realistic, stochastic, and local model that reproduces nonrelativistic quantum mechanics (QM) results without using its mathematical formulation. The proposed model only uses integer-valued quantities and operations on…

Quantum Physics · Physics 2018-01-17 Antonio Sciarretta

Markov Chain Monte Carlo (MCMC) techniques are now widely used for cosmological parameter estimation. Chains are generated to sample the posterior probability distribution obtained following the Bayesian approach. An important issue is how…

This tutorial article showcases the many varieties and uses of quantum walks. Discrete time quantum walks are introduced as counterparts of classical random walks. The emphasis is on the connections and differences between the two types of…

Quantum Physics · Physics 2013-05-16 Daniel Reitzner , Daniel Nagaj , Vladimir Buzek

Continuous-time Markov chains (CTMCs) are popular modeling formalism that constitutes the underlying semantics for real-time probabilistic systems such as queuing networks, stochastic process algebras, and calculi for systems biology. Prism…

Machine Learning · Computer Science 2023-02-20 Giovanni Bacci , Anna Ingólfsdóttir , Kim G. Larsen , Raphaël Reynouard

Quantum computers provide an opportunity to efficiently sample from probability distributions that include non-trivial interference effects between amplitudes. Using a simple process wherein all possible state histories can be specified by…

Quantum Physics · Physics 2019-08-22 Davide Provasoli , Benjamin Nachman , Wibe A. de Jong , Christian W Bauer

The one-way quantum computer (QCc) is a universal scheme of quantum computation consisting only of one-qubit measurements on a particular entangled multi-qubit state, the cluster state. The computational model underlying the QCc is…

Quantum Physics · Physics 2007-05-23 R. Raussendorf , H. J. Briegel

In the paper is discussed complete probabilistic description of quantum systems with application to multiqubit quantum computations. In simplest case it is a set of probabilities of transitions to some fixed set of states. The probabilities…

Quantum Physics · Physics 2007-05-23 Alexander Yu. Vlasov

We study a classical model for the accumulation of errors in multi-qubit quantum computations. By modeling the error process in a quantum computation using two coupled Markov chains, we are able to capture a weak form of time-dependency…

Quantum Physics · Physics 2021-04-26 Long Ma , Jaron Sanders

Quantum walks on graphs are ubiquitous in quantum computing finding a myriad of applications. Likewise, random walks on graphs are a fundamental building block for a large number of algorithms with diverse applications. While the…

Quantum Physics · Physics 2020-12-09 Matheus G. Andrade , Franklin Marquezino , Daniel R. Figueiredo

Many problems of practical interest rely on Continuous-time Markov chains~(CTMCs) defined over combinatorial state spaces, rendering the computation of transition probabilities, and hence probabilistic inference, difficult or impossible…