Result: Correlated Markov Quantum Walks

Title:
Correlated Markov Quantum Walks
Source:
Annales Henri Poincaré. 13(8):1767-1805
Publisher Information:
Heidelberg: Springer, 2012.
Publication Year:
2012
Physical Description:
print, 42 ref
Original Material:
INIST-CNRS
Subject Terms:
Mathematics, Mathématiques, Physics, Physique, Theoretical physics, Physique théorique, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Combinatoire. Structures ordonnées, Combinatorics. Ordered structures, Ordre, treillis, structures algébriques ordonnées, Order, lattices, ordered algebraic structures, Probabilités et statistiques, Probability and statistics, Théorie des probabilités et processus stochastiques, Probability theory and stochastic processes, Processus de markov, Markov processes, Statistiques, Statistics, Inférence à partir de processus stochastiques; analyse des séries temporelles, Inference from stochastic processes; time series analysis, Physique, Physics, Generalites, General, Méthodes mathématiques en physique, Mathematical methods in physics, Divers, Other topics in mathematical methods in physics, Analyse corrélation, Correlation analysis, Análisis correlación, Caractère aléatoire, Randomness, Centre, Center, Centro, Chaîne Markov, Markov chain, Cadena Markov, Degré liberté, Degrees of freedom, Diffusion, Scattering, Distribution aléatoire, Random distribution, Distribución aleatoria, Décalage, Shift, Decalaje, Equation diffusion, Diffusion equation, Ecuación difusión, Fonction caractéristique, Characteristic function, Función característica, Fonction distribution, Distribution functions, Fonction répartition, Distribution function, Función distribución, Grande déviation, Large deviation, Gran desviación, Loi limite, Limit distribution, Ley límite, Loi probabilité, Probability distribution, Ley probabilidad, Matrice aléatoire, Random matrix, Matriz aleatoria, Observable, Observables, Physique mathématique, Mathematical physics, Position, Positions, Puissance, Power, Suite aléatoire, Random sequences, Temps discret, Discrete time, Tiempo discreto, Treillis, Lattice, Enrejado, 06Bxx, 47A10, 60E05, 60E10, 60F10, 60F17, 60J10, 62E20, 62M02, Comportement temps long, Déviation modérée, Fonction Markov, Formule Feynman Kac, Loi stationnaire, Stationary distribution
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
Department of Physics Faculty of Science Cairo University, Cairo 12613, Egypt
UJF-Grenoble 1 CNRS, Institut Fourier, UMR 5582, 38402 Grenoble, France
ISSN:
1424-0637
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics

Theoretical physics
Accession Number:
edscal.26550080
Database:
PASCAL Archive

Further Information

We consider the discrete time unitary dynamics given by a quantum walk on ℤd performed by a particle with internal degree of freedom, called coin state, according to the following iterated rule: a unitary update of the coin state takes place, followed by a shift on the lattice, conditioned on the coin state of the particle. We study the large time behavior of the quantum mechanical probability distribution of the position observable in ℤd for random updates of the coin states of the following form. The random sequences of unitary updates are given by a site-dependent function of a Markov chain in time, with the following properties: on each site, they share the same stationary Markovian distribution and, for each fixed time, they form a deterministic periodic pattern on the lattice. We prove a Feynman―Kac formula to express the characteristic function of the averaged distribution over the randomness at time n in terms of the nth power of an operator M. By analyzing the spectrum of M, we show that this distribution possesses a drift proportional to the time and its centered counterpart displays a diffusive behavior with a diffusion matrix we compute. Moderate and large deviation principles are also proven to hold for the averaged distribution and the limit of the suitably rescaled corresponding characteristic function is shown to satisfy a diffusion equation. An example of random updates for which the analysis of the distribution can be performed without averaging is worked out. The random distribution displays a deterministic drift proportional to time and its centered counterpart gives rise to a random diffusion matrix, the law of which we compute. We complete the picture by presenting an uncorrelated example.