On Hidden States in Quantum Random Walks

It was recently pointed out that identifiability of quantum random walks and hidden Markov processes underlie the same principles. This analogy immediately raises questions on the existence of hidden states also in quantum random walks and their relationship with earlier debates on hidden states in quantum mechanics. The overarching insight was that not only hidden Markov processes, but also quantum random walks are finitary processes. Since finitary processes enjoy nice asymptotic properties, this also encourages to further investigate the asymptotic properties of quantum random walks. Here, answers to all these questions are given. Quantum random walks, hidden Markov processes and finitary processes are put into a unifying model context. In this context, quantum random walks are seen to not only enjoy nice ergodic properties in general, but also intuitive quantum-style asymptotic properties. It is also pointed out how hidden states arising from our framework relate to hidden states in earlier, prominent treatments on topics such as the EPR paradoxon or Bell's inequalities.Comment: 26 page

Asymptotic Mean Stationarity of Sources With Finite Evolution Dimension

The notion of the emph{evolution} of a discrete random source with finite alphabet is introduced and its behavior under the action of an associated linear emph{evolution operator} is studied. Viewing these sources as possibly stable dynamical systems it is proved that all random sources with finite evolution dimension are asymptotically mean stationary, which implies that such random sources have ergodic properties and a well-defined entropy rate. It is shown that the class of random sources with finite evolution dimension properly generalizes the well-studied class of finitary stochastic processes, which includes (hidden) Markov sources as special cases

On analytic properties of entropy rate

Entropy rate of discrete random sources are a real valued functional on the space of probability measures associated with the random sources. If one equips this space with a topology one can ask for the analytic properties of the entropy rates. A natural choice is the topology, which is induced by the norm of total variation. A central result is that entropy rate is Lipschitz continuous relative to this topology. The consequences are manifold. First, corollaries are obtained that refer to prevalent objects of probability theory. Second, the result is extended to entropy rate of dynamical systems. Third, it is shown how to exploit the proof schemes to give a direct and elementary proof for the existence of entropy rate of asymptotically mean stationary random sources

Characterization of ergodic hidden Markov sources

An algebraic criterim for the ergodicity of discrete random sources is presented. For finite-dimensional sources, which contain hidden Markov sources as a subclass, the criterium can be effectively computed. This result is obtained on the background of a novel, elementary theory of discrete random sources, which is based on linear spaces spanned by word functions, and linear operators on these spaces. An outline of basic elements of this theory is provided

Quantum Predictor Models

We define a class of finitely parameterizable stochastic models, Quantum Predictor Models (QPMs), such that, in an obvious manner, a collection of prevalent quantum statistical phenomena can be described by their means. Moreover, we identify the induced class of discrete random processes with the class of finite-dimensional processes, which enjoy nice ergodic properties and a graphical representation. For the subclass of Quantum Markov Chains (QMCs), which reflect most of the real-world quantum processes, we can give an even stronger version of the ergodic theorem available for general QPMs, thereby also strengthening an ergodic theorem, which has recently been proved for the class of Quantum Walks on Graphs